v1

filelists/ljs_audio_text_val_filelist.txt

+DUMMY1/LJ022-0023.wav|The overwhelming majority of people in this country know how to sift the wheat from the chaff in what they hear and what they read.
+DUMMY1/LJ043-0030.wav|If somebody did that to me, a lousy trick like that, to take my wife away, and all the furniture, I would be mad as hell, too.
+DUMMY1/LJ005-0201.wav|as is shown by the report of the Commissioners to inquire into the state of the municipal corporations in eighteen thirty-five.
+DUMMY1/LJ001-0110.wav|Even the Caslon type when enlarged shows great shortcomings in this respect:
+DUMMY1/LJ003-0345.wav|All the committee could do in this respect was to throw the responsibility on others.
+DUMMY1/LJ007-0154.wav|These pungent and well-grounded strictures applied with still greater force to the unconvicted prisoner, the man who came to the prison innocent, and still uncontaminated,
+DUMMY1/LJ018-0098.wav|and recognized as one of the frequenters of the bogus law-stationers. His arrest led to that of others.
+DUMMY1/LJ047-0044.wav|Oswald was, however, willing to discuss his contacts with Soviet authorities. He denied having any involvement with Soviet intelligence agencies
+DUMMY1/LJ031-0038.wav|The first physician to see the President at Parkland Hospital was Dr. Charles J. Carrico, a resident in general surgery.
+DUMMY1/LJ048-0194.wav|during the morning of November twenty-two prior to the motorcade.
+DUMMY1/LJ049-0026.wav|On occasion the Secret Service has been permitted to have an agent riding in the passenger compartment with the President.
+DUMMY1/LJ004-0152.wav|although at Mr. Buxton's visit a new jail was in process of erection, the first step towards reform since Howard's visitation in seventeen seventy-four.
+DUMMY1/LJ008-0278.wav|or theirs might be one of many, and it might be considered necessary to "make an example."
+DUMMY1/LJ043-0002.wav|The Warren Commission Report. By The President's Commission on the Assassination of President Kennedy. Chapter seven. Lee Harvey Oswald:
+DUMMY1/LJ009-0114.wav|Mr. Wakefield winds up his graphic but somewhat sensational account by describing another religious service, which may appropriately be inserted here.
+DUMMY1/LJ028-0506.wav|A modern artist would have difficulty in doing such accurate work.
+DUMMY1/LJ050-0168.wav|with the particular purposes of the agency involved. The Commission recognizes that this is a controversial area
+DUMMY1/LJ039-0223.wav|Oswald's Marine training in marksmanship, his other rifle experience and his established familiarity with this particular weapon
+DUMMY1/LJ029-0032.wav|According to O'Donnell, quote, we had a motorcade wherever we went, end quote.
+DUMMY1/LJ031-0070.wav|Dr. Clark, who most closely observed the head wound,
+DUMMY1/LJ034-0198.wav|Euins, who was on the southwest corner of Elm and Houston Streets testified that he could not describe the man he saw in the window.
+DUMMY1/LJ026-0068.wav|Energy enters the plant, to a small extent,
+DUMMY1/LJ039-0075.wav|once you know that you must put the crosshairs on the target and that is all that is necessary.
+DUMMY1/LJ004-0096.wav|the fatal consequences whereof might be prevented if the justices of the peace were duly authorized
+DUMMY1/LJ005-0014.wav|Speaking on a debate on prison matters, he declared that
+DUMMY1/LJ012-0161.wav|he was reported to have fallen away to a shadow.
+DUMMY1/LJ018-0239.wav|His disappearance gave color and substance to evil reports already in circulation that the will and conveyance above referred to
+DUMMY1/LJ019-0257.wav|Here the tread-wheel was in use, there cellular cranks, or hard-labor machines.
+DUMMY1/LJ028-0008.wav|you tap gently with your heel upon the shoulder of the dromedary to urge her on.
+DUMMY1/LJ024-0083.wav|This plan of mine is no attack on the Court;
+DUMMY1/LJ042-0129.wav|No night clubs or bowling alleys, no places of recreation except the trade union dances. I have had enough.
+DUMMY1/LJ036-0103.wav|The police asked him whether he could pick out his passenger from the lineup.
+DUMMY1/LJ046-0058.wav|During his Presidency, Franklin D. Roosevelt made almost four hundred journeys and traveled more than three hundred fifty thousand miles.
+DUMMY1/LJ014-0076.wav|He was seen afterwards smoking and talking with his hosts in their back parlor, and never seen again alive.
+DUMMY1/LJ002-0043.wav|long narrow rooms -- one thirty-six feet, six twenty-three feet, and the eighth eighteen,
+DUMMY1/LJ009-0076.wav|We come to the sermon.
+DUMMY1/LJ017-0131.wav|even when the high sheriff had told him there was no possibility of a reprieve, and within a few hours of execution.
+DUMMY1/LJ046-0184.wav|but there is a system for the immediate notification of the Secret Service by the confining institution when a subject is released or escapes.
+DUMMY1/LJ014-0263.wav|When other pleasures palled he took a theatre, and posed as a munificent patron of the dramatic art.
+DUMMY1/LJ042-0096.wav|(old exchange rate) in addition to his factory salary of approximately equal amount
+DUMMY1/LJ049-0050.wav|Hill had both feet on the car and was climbing aboard to assist President and Mrs. Kennedy.
+DUMMY1/LJ019-0186.wav|seeing that since the establishment of the Central Criminal Court, Newgate received prisoners for trial from several counties,
+DUMMY1/LJ028-0307.wav|then let twenty days pass, and at the end of that time station near the Chaldasan gates a body of four thousand.
+DUMMY1/LJ012-0235.wav|While they were in a state of insensibility the murder was committed.
+DUMMY1/LJ034-0053.wav|reached the same conclusion as Latona that the prints found on the cartons were those of Lee Harvey Oswald.
+DUMMY1/LJ014-0030.wav|These were damnatory facts which well supported the prosecution.
+DUMMY1/LJ015-0203.wav|but were the precautions too minute, the vigilance too close to be eluded or overcome?
+DUMMY1/LJ028-0093.wav|but his scribe wrote it in the manner customary for the scribes of those days to write of their royal masters.
+DUMMY1/LJ002-0018.wav|The inadequacy of the jail was noticed and reported upon again and again by the grand juries of the city of London,
+DUMMY1/LJ028-0275.wav|At last, in the twentieth month,
+DUMMY1/LJ012-0042.wav|which he kept concealed in a hiding-place with a trap-door just under his bed.
+DUMMY1/LJ011-0096.wav|He married a lady also belonging to the Society of Friends, who brought him a large fortune, which, and his own money, he put into a city firm,
+DUMMY1/LJ036-0077.wav|Roger D. Craig, a deputy sheriff of Dallas County,
+DUMMY1/LJ016-0318.wav|Other officials, great lawyers, governors of prisons, and chaplains supported this view.
+DUMMY1/LJ013-0164.wav|who came from his room ready dressed, a suspicious circumstance, as he was always late in the morning.
+DUMMY1/LJ027-0141.wav|is closely reproduced in the life-history of existing deer. Or, in other words,
+DUMMY1/LJ028-0335.wav|accordingly they committed to him the command of their whole army, and put the keys of their city into his hands.
+DUMMY1/LJ031-0202.wav|Mrs. Kennedy chose the hospital in Bethesda for the autopsy because the President had served in the Navy.
+DUMMY1/LJ021-0145.wav|From those willing to join in establishing this hoped-for period of peace,
+DUMMY1/LJ016-0288.wav|"Müller, Müller, He's the man," till a diversion was created by the appearance of the gallows, which was received with continuous yells.
+DUMMY1/LJ028-0081.wav|Years later, when the archaeologists could readily distinguish the false from the true,
+DUMMY1/LJ018-0081.wav|his defense being that he had intended to commit suicide, but that, on the appearance of this officer who had wronged him,
+DUMMY1/LJ021-0066.wav|together with a great increase in the payrolls, there has come a substantial rise in the total of industrial profits
+DUMMY1/LJ009-0238.wav|After this the sheriffs sent for another rope, but the spectators interfered, and the man was carried back to jail.
+DUMMY1/LJ005-0079.wav|and improve the morals of the prisoners, and shall insure the proper measure of punishment to convicted offenders.
+DUMMY1/LJ035-0019.wav|drove to the northwest corner of Elm and Houston, and parked approximately ten feet from the traffic signal.
+DUMMY1/LJ036-0174.wav|This is the approximate time he entered the roominghouse, according to Earlene Roberts, the housekeeper there.
+DUMMY1/LJ046-0146.wav|The criteria in effect prior to November twenty-two, nineteen sixty-three, for determining whether to accept material for the PRS general files
+DUMMY1/LJ017-0044.wav|and the deepest anxiety was felt that the crime, if crime there had been, should be brought home to its perpetrator.
+DUMMY1/LJ017-0070.wav|but his sporting operations did not prosper, and he became a needy man, always driven to desperate straits for cash.
+DUMMY1/LJ014-0020.wav|He was soon afterwards arrested on suspicion, and a search of his lodgings brought to light several garments saturated with blood;
+DUMMY1/LJ016-0020.wav|He never reached the cistern, but fell back into the yard, injuring his legs severely.
+DUMMY1/LJ045-0230.wav|when he was finally apprehended in the Texas Theatre. Although it is not fully corroborated by others who were present,
+DUMMY1/LJ035-0129.wav|and she must have run down the stairs ahead of Oswald and would probably have seen or heard him.
+DUMMY1/LJ008-0307.wav|afterwards express a wish to murder the Recorder for having kept them so long in suspense.
+DUMMY1/LJ008-0294.wav|nearly indefinitely deferred.
+DUMMY1/LJ047-0148.wav|On October twenty-five,
+DUMMY1/LJ008-0111.wav|They entered a "stone cold room," and were presently joined by the prisoner.
+DUMMY1/LJ034-0042.wav|that he could only testify with certainty that the print was less than three days old.
+DUMMY1/LJ037-0234.wav|Mrs. Mary Brock, the wife of a mechanic who worked at the station, was there at the time and she saw a white male,
+DUMMY1/LJ040-0002.wav|Chapter seven. Lee Harvey Oswald: Background and Possible Motives, Part one.
+DUMMY1/LJ045-0140.wav|The arguments he used to justify his use of the alias suggest that Oswald may have come to think that the whole world was becoming involved
+DUMMY1/LJ012-0035.wav|the number and names on watches, were carefully removed or obliterated after the goods passed out of his hands.
+DUMMY1/LJ012-0250.wav|On the seventh July, eighteen thirty-seven,
+DUMMY1/LJ016-0179.wav|contracted with sheriffs and conveners to work by the job.
+DUMMY1/LJ016-0138.wav|at a distance from the prison.
+DUMMY1/LJ027-0052.wav|These principles of homology are essential to a correct interpretation of the facts of morphology.
+DUMMY1/LJ031-0134.wav|On one occasion Mrs. Johnson, accompanied by two Secret Service agents, left the room to see Mrs. Kennedy and Mrs. Connally.
+DUMMY1/LJ019-0273.wav|which Sir Joshua Jebb told the committee he considered the proper elements of penal discipline.
+DUMMY1/LJ014-0110.wav|At the first the boxes were impounded, opened, and found to contain many of O'Connor's effects.
+DUMMY1/LJ034-0160.wav|on Brennan's subsequent certain identification of Lee Harvey Oswald as the man he saw fire the rifle.
+DUMMY1/LJ038-0199.wav|eleven. If I am alive and taken prisoner,
+DUMMY1/LJ014-0010.wav|yet he could not overcome the strange fascination it had for him, and remained by the side of the corpse till the stretcher came.
+DUMMY1/LJ033-0047.wav|I noticed when I went out that the light was on, end quote,
+DUMMY1/LJ040-0027.wav|He was never satisfied with anything.
+DUMMY1/LJ048-0228.wav|and others who were present say that no agent was inebriated or acted improperly.
+DUMMY1/LJ003-0111.wav|He was in consequence put out of the protection of their internal law, end quote. Their code was a subject of some curiosity.
+DUMMY1/LJ008-0258.wav|Let me retrace my steps, and speak more in detail of the treatment of the condemned in those bloodthirsty and brutally indifferent days,
+DUMMY1/LJ029-0022.wav|The original plan called for the President to spend only one day in the State, making whirlwind visits to Dallas, Fort Worth, San Antonio, and Houston.
+DUMMY1/LJ004-0045.wav|Mr. Sturges Bourne, Sir James Mackintosh, Sir James Scarlett, and William Wilberforce.

filelists/ljs_audio_text_val_filelist.txt.cleaned

+DUMMY1/LJ022-0023.wav|ðɪ ˌoʊvɚwˈɛlmɪŋ mədʒˈɔːɹɪɾi ʌv pˈiːpəl ɪn ðɪs kˈʌntɹi nˈoʊ hˌaʊ tə sˈɪft ðə wˈiːt fɹʌmðə tʃˈæf ɪn wˌʌt ðeɪ hˈɪɹ ænd wˌʌt ðeɪ ɹˈiːd.
+DUMMY1/LJ043-0030.wav|ɪf sˈʌmbɑːdi dˈɪd ðˈæt tə mˌiː, ɐ lˈaʊsi tɹˈɪk lˈaɪk ðˈæt, tə tˈeɪk maɪ wˈaɪf ɐwˈeɪ, ænd ˈɔːl ðə fˈɜːnɪtʃɚ, ˈaɪ wʊd biː mˈæd æz hˈɛl, tˈuː.
+DUMMY1/LJ005-0201.wav|ˌæzˌɪz ʃˈoʊn baɪ ðə ɹɪpˈoːɹt ʌvðə kəmˈɪʃənɚz tʊ ɪnkwˈaɪɚɹ ˌɪntʊ ðə stˈeɪt ʌvðə mjuːnˈɪsɪpəl kˌɔːɹpɚɹˈeɪʃənz ɪn eɪtˈiːn θˈɜːɾifˈaɪv.
+DUMMY1/LJ001-0110.wav|ˈiːvən ðə kˈæslɑːn tˈaɪp wɛn ɛnlˈɑːɹdʒd ʃˈoʊz ɡɹˈeɪt ʃˈɔːɹtkʌmɪŋz ɪn ðɪs ɹɪspˈɛkt:
+DUMMY1/LJ003-0345.wav|ˈɔːl ðə kəmˈɪɾi kʊd dˈuː ɪn ðɪs ɹɪspˈɛkt wʌz tə θɹˈoʊ ðə ɹɪspˌɑːnsəbˈɪlɪɾi ˌɑːn ˈʌðɚz.
+DUMMY1/LJ007-0154.wav|ðiːz pˈʌndʒənt ænd wˈɛlɡɹˈaʊndᵻd stɹˈɪktʃɚz ɐplˈaɪd wɪð stˈɪl ɡɹˈeɪɾɚ fˈoːɹs tə ðɪ ʌnkənvˈɪktᵻd pɹˈɪzənɚ, ðə mˈæn hˌuː kˈeɪm tə ðə pɹˈɪzən ˈɪnəsənt, ænd stˈɪl ʌnkəntˈæmᵻnˌeɪɾᵻd,
+DUMMY1/LJ018-0098.wav|ænd ɹˈɛkəɡnˌaɪzd æz wˈʌn ʌvðə fɹˈiːkwɛntɚz ʌvðə bˈoʊɡəs lˈɔːstˈeɪʃənɚz. hɪz ɐɹˈɛst lˈɛd tə ðæt ʌv ˈʌðɚz.
+DUMMY1/LJ047-0044.wav|ˈɑːswəld wʌz, haʊˈɛvɚ, wˈɪlɪŋ tə dɪskˈʌs hɪz kˈɑːntækts wɪð sˈoʊviət ɐθˈɔːɹɪɾiz. hiː dɪnˈaɪd hˌævɪŋ ˌɛni ɪnvˈɑːlvmənt wɪð sˈoʊviət ɪntˈɛlɪdʒəns ˈeɪdʒənsiz
+DUMMY1/LJ031-0038.wav|ðə fˈɜːst fɪzˈɪʃən tə sˈiː ðə pɹˈɛzɪdənt æt pˈɑːɹklənd hˈɑːspɪɾəl wʌz dˈɑːktɚ tʃˈɑːɹlz dʒˈeɪ. kˈæɹɪkˌoʊ, ɐ ɹˈɛzɪdənt ɪn dʒˈɛnɚɹəl sˈɜːdʒɚɹi.
+DUMMY1/LJ048-0194.wav|dˈʊɹɪŋ ðə mˈɔːɹnɪŋ ʌv noʊvˈɛmbɚ twˈɛntitˈuː pɹˈaɪɚ tə ðə mˈoʊɾɚkˌeɪd.
+DUMMY1/LJ049-0026.wav|ˌɑːn əkˈeɪʒən ðə sˈiːkɹət sˈɜːvɪs hɐzbɪn pɚmˈɪɾᵻd tə hæv ɐn ˈeɪdʒənt ɹˈaɪdɪŋ ɪnðə pˈæsɪndʒɚ kəmpˈɑːɹtmənt wɪððə pɹˈɛzɪdənt.
+DUMMY1/LJ004-0152.wav|ɑːlðˈoʊ æt mˈɪstɚ bˈʌkstənz vˈɪzɪt ɐ nˈuː dʒˈeɪl wʌz ɪn pɹˈɑːsɛs ʌv ɪɹˈɛkʃən, ðə fˈɜːst stˈɛp tʊwˈɔːɹdz ɹɪfˈɔːɹm sˈɪns hˈaʊɚdz vˌɪzɪtˈeɪʃən ɪn sˌɛvəntˈiːn sˈɛvəntifˈoːɹ.
+DUMMY1/LJ008-0278.wav|ɔːɹ ðˈɛɹz mˌaɪt biː wˈʌn ʌv mˈɛni, ænd ɪt mˌaɪt biː kənsˈɪdɚd nˈɛsəsɚɹi tuː "mˌeɪk ɐn ɛɡzˈæmpəl."
+DUMMY1/LJ043-0002.wav|ðə wˈɔːɹən kəmˈɪʃən ɹɪpˈoːɹt. baɪ ðə pɹˈɛzɪdənts kəmˈɪʃən ɑːnðɪ ɐsˌæsᵻnˈeɪʃən ʌv pɹˈɛzɪdənt kˈɛnədi. tʃˈæptɚ sˈɛvən. lˈiː hˈɑːɹvi ˈɑːswəld:
+DUMMY1/LJ009-0114.wav|mˈɪstɚ wˈeɪkfiːld wˈaɪndz ˈʌp hɪz ɡɹˈæfɪk bˌʌt sˈʌmwʌt sɛnsˈeɪʃənəl ɐkˈaʊnt baɪ dɪskɹˈaɪbɪŋ ɐnˈʌðɚ ɹɪlˈɪdʒəs sˈɜːvɪs, wˌɪtʃ mˈeɪ ɐpɹˈoʊpɹɪətli biː ɪnsˈɜːɾᵻd hˈɪɹ.
+DUMMY1/LJ028-0506.wav|ɐ mˈɑːdɚn ˈɑːɹɾɪst wʊdhɐv dˈɪfɪkˌʌlti ɪn dˌuːɪŋ sˈʌtʃ ˈækjʊɹət wˈɜːk.
+DUMMY1/LJ050-0168.wav|wɪððə pɚtˈɪkjʊlɚ pˈɜːpəsᵻz ʌvðɪ ˈeɪdʒənsi ɪnvˈɑːlvd. ðə kəmˈɪʃən ɹˈɛkəɡnˌaɪzɪz ðæt ðɪs ɪz ɐ kˌɑːntɹəvˈɜːʃəl ˈɛɹiə
+DUMMY1/LJ039-0223.wav|ˈɑːswəldz mɚɹˈiːn tɹˈeɪnɪŋ ɪn mˈɑːɹksmənʃˌɪp, hɪz ˈʌðɚ ɹˈaɪfəl ɛkspˈiəɹɪəns ænd hɪz ɪstˈæblɪʃt fəmˌɪlɪˈæɹɪɾi wɪð ðɪs pɚtˈɪkjʊlɚ wˈɛpən
+DUMMY1/LJ029-0032.wav|ɐkˈoːɹdɪŋ tʊ oʊdˈɑːnəl, kwˈoʊt, wiː hɐd ɐ mˈoʊɾɚkˌeɪd wɛɹɹˈɛvɚ wiː wˈɛnt, ˈɛnd kwˈoʊt.
+DUMMY1/LJ031-0070.wav|dˈɑːktɚ klˈɑːɹk, hˌuː mˈoʊst klˈoʊsli ɑːbzˈɜːvd ðə hˈɛd wˈuːnd,
+DUMMY1/LJ034-0198.wav|jˈuːɪnz, hˌuː wʌz ɑːnðə saʊθwˈɛst kˈɔːɹnɚɹ ʌv ˈɛlm ænd hjˈuːstən stɹˈiːts tˈɛstɪfˌaɪd ðæt hiː kʊd nˌɑːt dɪskɹˈaɪb ðə mˈæn hiː sˈɔː ɪnðə wˈɪndoʊ.
+DUMMY1/LJ026-0068.wav|ˈɛnɚdʒi ˈɛntɚz ðə plˈænt, tʊ ɐ smˈɔːl ɛkstˈɛnt,
+DUMMY1/LJ039-0075.wav|wˈʌns juː nˈoʊ ðæt juː mˈʌst pˌʊt ðə kɹˈɔshɛɹz ɑːnðə tˈɑːɹɡɪt ænd ðæt ɪz ˈɔːl ðæt ɪz nˈɛsəsɚɹi.
+DUMMY1/LJ004-0096.wav|ðə fˈeɪɾəl kˈɑːnsɪkwənsᵻz wˈɛɹɑːf mˌaɪt biː pɹɪvˈɛntᵻd ɪf ðə dʒˈʌstɪsᵻz ʌvðə pˈiːs wɜː djˈuːli ˈɔːθɚɹˌaɪzd
+DUMMY1/LJ005-0014.wav|spˈiːkɪŋ ˌɑːn ɐ dɪbˈeɪt ˌɑːn pɹˈɪzən mˈæɾɚz, hiː dᵻklˈɛɹd ðˈæt
+DUMMY1/LJ012-0161.wav|hiː wʌz ɹɪpˈoːɹɾᵻd tə hæv fˈɔːlən ɐwˈeɪ tʊ ɐ ʃˈædoʊ.
+DUMMY1/LJ018-0239.wav|hɪz dˌɪsɐpˈɪɹəns ɡˈeɪv kˈʌlɚ ænd sˈʌbstəns tʊ ˈiːvəl ɹɪpˈoːɹts ɔːlɹˌɛdi ɪn sˌɜːkjʊlˈeɪʃən ðætðə wɪl ænd kənvˈeɪəns əbˌʌv ɹɪfˈɜːd tuː
+DUMMY1/LJ019-0257.wav|hˈɪɹ ðə tɹˈɛdwˈiːl wʌz ɪn jˈuːs, ðɛɹ sˈɛljʊlɚ kɹˈæŋks, ɔːɹ hˈɑːɹdlˈeɪbɚ məʃˈiːnz.
+DUMMY1/LJ028-0008.wav|juː tˈæp dʒˈɛntli wɪð jʊɹ hˈiːl əpˌɑːn ðə ʃˈoʊldɚɹ ʌvðə dɹˈoʊmdɚɹi tʊ ˈɜːdʒ hɜːɹ ˈɑːn.
+DUMMY1/LJ024-0083.wav|ðɪs plˈæn ʌv mˈaɪn ɪz nˈoʊ ɐtˈæk ɑːnðə kˈoːɹt;
+DUMMY1/LJ042-0129.wav|nˈoʊ nˈaɪt klˈʌbz ɔːɹ bˈoʊlɪŋ ˈælɪz, nˈoʊ plˈeɪsᵻz ʌv ɹˌɛkɹiːˈeɪʃən ɛksˈɛpt ðə tɹˈeɪd jˈuːniən dˈænsᵻz. ˈaɪ hæv hɐd ɪnˈʌf.
+DUMMY1/LJ036-0103.wav|ðə pəlˈiːs ˈæskt hˌɪm wˈɛðɚ hiː kʊd pˈɪk ˈaʊt hɪz pˈæsɪndʒɚ fɹʌmðə lˈaɪnʌp.
+DUMMY1/LJ046-0058.wav|dˈʊɹɪŋ hɪz pɹˈɛzɪdənsi, fɹˈæŋklɪn dˈiː. ɹˈoʊzəvˌɛlt mˌeɪd ˈɔːlmoʊst fˈoːɹ hˈʌndɹəd dʒˈɜːnɪz ænd tɹˈævəld mˈoːɹ ðɐn θɹˈiː hˈʌndɹəd fˈɪfti θˈaʊzənd mˈaɪlz.
+DUMMY1/LJ014-0076.wav|hiː wʌz sˈiːn ˈæftɚwɚdz smˈoʊkɪŋ ænd tˈɔːkɪŋ wɪð hɪz hˈoʊsts ɪn ðɛɹ bˈæk pˈɑːɹlɚ, ænd nˈɛvɚ sˈiːn ɐɡˈɛn ɐlˈaɪv.
+DUMMY1/LJ002-0043.wav|lˈɑːŋ nˈæɹoʊ ɹˈuːmz wˈʌn θˈɜːɾisˈɪks fˈiːt, sˈɪks twˈɛntiθɹˈiː fˈiːt, ænd ðɪ ˈeɪtθ eɪtˈiːn,
+DUMMY1/LJ009-0076.wav|wiː kˈʌm tə ðə sˈɜːmən.
+DUMMY1/LJ017-0131.wav|ˈiːvən wɛn ðə hˈaɪ ʃˈɛɹɪf hɐd tˈoʊld hˌɪm ðɛɹwˌʌz nˈoʊ pˌɑːsəbˈɪlɪɾi əvɚ ɹɪpɹˈiːv, ænd wɪðˌɪn ɐ fjˈuː ˈaɪʊɹz ʌv ˌɛksɪkjˈuːʃən.
+DUMMY1/LJ046-0184.wav|bˌʌt ðɛɹ ɪz ɐ sˈɪstəm fɚðɪ ɪmˈiːdɪət nˌoʊɾɪfɪkˈeɪʃən ʌvðə sˈiːkɹət sˈɜːvɪs baɪ ðə kənfˈaɪnɪŋ ˌɪnstɪtˈuːʃən wɛn ɐ sˈʌbdʒɛkt ɪz ɹɪlˈiːsd ɔːɹ ɛskˈeɪps.
+DUMMY1/LJ014-0263.wav|wˌɛn ˈʌðɚ plˈɛʒɚz pˈɔːld hiː tˈʊk ɐ θˈiəɾɚ, ænd pˈoʊzd æz ɐ mjuːnˈɪfɪsənt pˈeɪtɹən ʌvðə dɹəmˈæɾɪk ˈɑːɹt.
+DUMMY1/LJ042-0096.wav| ˈoʊld ɛkstʃˈeɪndʒ ɹˈeɪt ɪn ɐdˈɪʃən tə hɪz fˈæktɚɹi sˈælɚɹi ʌv ɐpɹˈɑːksɪmətli ˈiːkwəl ɐmˈaʊnt
+DUMMY1/LJ049-0050.wav|hˈɪl hɐd bˈoʊθ fˈiːt ɑːnðə kˈɑːɹ ænd wʌz klˈaɪmɪŋ ɐbˈoːɹd tʊ ɐsˈɪst pɹˈɛzɪdənt ænd mɪsˈɛs kˈɛnədi.
+DUMMY1/LJ019-0186.wav|sˈiːɪŋ ðæt sˈɪns ðɪ ɪstˈæblɪʃmənt ʌvðə sˈɛntɹəl kɹˈɪmɪnəl kˈoːɹt, nˈuːɡeɪt ɹɪsˈiːvd pɹˈɪzənɚz fɔːɹ tɹˈaɪəl fɹʌm sˈɛvɹəl kˈaʊntɪz,
+DUMMY1/LJ028-0307.wav|ðˈɛn lˈɛt twˈɛnti dˈeɪz pˈæs, ænd æt ðɪ ˈɛnd ʌv ðæt tˈaɪm stˈeɪʃən nˌɪɹ ðə tʃˈældæsən ɡˈeɪts ɐ bˈɑːdi ʌv fˈoːɹ θˈaʊzənd.
+DUMMY1/LJ012-0235.wav|wˌaɪl ðeɪ wɜːɹ ɪn ɐ stˈeɪt ʌv ɪnsˌɛnsəbˈɪlɪɾi ðə mˈɜːdɚ wʌz kəmˈɪɾᵻd.
+DUMMY1/LJ034-0053.wav|ɹˈiːtʃt ðə sˈeɪm kənklˈuːʒən æz lætˈoʊnə ðætðə pɹˈɪnts fˈaʊnd ɑːnðə kˈɑːɹtənz wɜː ðoʊz ʌv lˈiː hˈɑːɹvi ˈɑːswəld.
+DUMMY1/LJ014-0030.wav|ðiːz wɜː dˈæmnətˌoːɹi fˈækts wˌɪtʃ wˈɛl səpˈoːɹɾᵻd ðə pɹˌɑːsɪkjˈuːʃən.
+DUMMY1/LJ015-0203.wav|bˌʌt wɜː ðə pɹɪkˈɔːʃənz tˈuː mˈɪnɪt, ðə vˈɪdʒɪləns tˈuː klˈoʊs təbi ɪlˈuːdᵻd ɔːɹ ˌoʊvɚkˈʌm?
+DUMMY1/LJ028-0093.wav|bˌʌt hɪz skɹˈaɪb ɹˈoʊt ɪt ɪnðə mˈænɚ kˈʌstəmˌɛɹi fɚðə skɹˈaɪbz ʌv ðoʊz dˈeɪz tə ɹˈaɪt ʌv ðɛɹ ɹˈɔɪəl mˈæstɚz.
+DUMMY1/LJ002-0018.wav|ðɪ ɪnˈædɪkwəsi ʌvðə dʒˈeɪl wʌz nˈoʊɾɪsd ænd ɹɪpˈoːɹɾᵻd əpˌɑːn ɐɡˈɛn ænd ɐɡˈɛn baɪ ðə ɡɹˈænd dʒˈʊɹɪz ʌvðə sˈɪɾi ʌv lˈʌndən,
+DUMMY1/LJ028-0275.wav|æt lˈæst, ɪnðə twˈɛntiəθ mˈʌnθ,
+DUMMY1/LJ012-0042.wav|wˌɪtʃ hiː kˈɛpt kənsˈiːld ɪn ɐ hˈaɪdɪŋplˈeɪs wɪð ɐ tɹˈæpdˈoːɹ dʒˈʌst ˌʌndɚ hɪz bˈɛd.
+DUMMY1/LJ011-0096.wav|hiː mˈæɹɪd ɐ lˈeɪdi ˈɑːlsoʊ bɪlˈɑːŋɪŋ tə ðə səsˈaɪəɾi ʌv fɹˈɛndz, hˌuː bɹˈɔːt hˌɪm ɐ lˈɑːɹdʒ fˈɔːɹtʃən, wˈɪtʃ, ænd hɪz ˈoʊn mˈʌni, hiː pˌʊt ˌɪntʊ ɐ sˈɪɾi fˈɜːm,
+DUMMY1/LJ036-0077.wav|ɹˈɑːdʒɚ dˈiː. kɹˈeɪɡ, ɐ dˈɛpjuːɾi ʃˈɛɹɪf ʌv dˈæləs kˈaʊnti,
+DUMMY1/LJ016-0318.wav|ˈʌðɚɹ əfˈɪʃəlz, ɡɹˈeɪt lˈɔɪɚz, ɡˈʌvɚnɚz ʌv pɹˈɪzənz, ænd tʃˈæplɪnz səpˈoːɹɾᵻd ðɪs vjˈuː.
+DUMMY1/LJ013-0164.wav|hˌuː kˈeɪm fɹʌm hɪz ɹˈuːm ɹˈɛdi dɹˈɛst, ɐ səspˈɪʃəs sˈɜːkəmstˌæns, æz hiː wʌz ˈɔːlweɪz lˈeɪt ɪnðə mˈɔːɹnɪŋ.
+DUMMY1/LJ027-0141.wav|ɪz klˈoʊsli ɹɪpɹədˈuːst ɪnðə lˈaɪfhˈɪstɚɹi ʌv ɛɡzˈɪstɪŋ dˈɪɹ. ˈɔːɹ, ɪn ˈʌðɚ wˈɜːdz,
+DUMMY1/LJ028-0335.wav|ɐkˈoːɹdɪŋli ðeɪ kəmˈɪɾᵻd tə hˌɪm ðə kəmˈænd ʌv ðɛɹ hˈoʊl ˈɑːɹmi, ænd pˌʊt ðə kˈiːz ʌv ðɛɹ sˈɪɾi ˌɪntʊ hɪz hˈændz.
+DUMMY1/LJ031-0202.wav|mɪsˈɛs kˈɛnədi tʃˈoʊz ðə hˈɑːspɪɾəl ɪn bəθˈɛzdə fɚðɪ ˈɔːtɑːpsi bɪkˈʌz ðə pɹˈɛzɪdənt hɐd sˈɜːvd ɪnðə nˈeɪvi.
+DUMMY1/LJ021-0145.wav|fɹʌm ðoʊz wˈɪlɪŋ tə dʒˈɔɪn ɪn ɪstˈæblɪʃɪŋ ðɪs hˈoʊptfɔːɹ pˈiəɹɪəd ʌv pˈiːs,
+DUMMY1/LJ016-0288.wav|"mˈʌlɚ, mˈʌlɚ, hiːz ðə mˈæn," tˈɪl ɐ daɪvˈɜːʒən wʌz kɹiːˈeɪɾᵻd baɪ ðɪ ɐpˈɪɹəns ʌvðə ɡˈæloʊz, wˌɪtʃ wʌz ɹɪsˈiːvd wɪð kəntˈɪnjuːəs jˈɛlz.
+DUMMY1/LJ028-0081.wav|jˈɪɹz lˈeɪɾɚ, wˌɛn ðɪ ˌɑːɹkiːˈɑːlədʒˌɪsts kʊd ɹˈɛdɪli dɪstˈɪŋɡwɪʃ ðə fˈɑːls fɹʌmðə tɹˈuː,
+DUMMY1/LJ018-0081.wav|hɪz dɪfˈɛns bˌiːɪŋ ðæt hiː hɐd ɪntˈɛndᵻd tə kəmˈɪt sˈuːɪsˌaɪd, bˌʌt ðˈæt, ɑːnðɪ ɐpˈɪɹəns ʌv ðɪs ˈɑːfɪsɚ hˌuː hɐd ɹˈɔŋd hˌɪm,
+DUMMY1/LJ021-0066.wav|təɡˌɛðɚ wɪð ɐ ɡɹˈeɪt ˈɪnkɹiːs ɪnðə pˈeɪɹoʊlz, ðɛɹ hɐz kˈʌm ɐ səbstˈænʃəl ɹˈaɪz ɪnðə tˈoʊɾəl ʌv ɪndˈʌstɹɪəl pɹˈɑːfɪts
+DUMMY1/LJ009-0238.wav|ˈæftɚ ðɪs ðə ʃˈɛɹɪfs sˈɛnt fɔːɹ ɐnˈʌðɚ ɹˈoʊp, bˌʌt ðə spɛktˈeɪɾɚz ˌɪntəfˈɪɹd, ænd ðə mˈæn wʌz kˈæɹɪd bˈæk tə dʒˈeɪl.
+DUMMY1/LJ005-0079.wav|ænd ɪmpɹˈuːv ðə mˈɔːɹəlz ʌvðə pɹˈɪzənɚz, ænd ʃˌæl ɪnʃˈʊɹ ðə pɹˈɑːpɚ mˈɛʒɚɹ ʌv pˈʌnɪʃmənt tə kənvˈɪktᵻd əfˈɛndɚz.
+DUMMY1/LJ035-0019.wav|dɹˈoʊv tə ðə nɔːɹθwˈɛst kˈɔːɹnɚɹ ʌv ˈɛlm ænd hjˈuːstən, ænd pˈɑːɹkt ɐpɹˈɑːksɪmətli tˈɛn fˈiːt fɹʌmðə tɹˈæfɪk sˈɪɡnəl.
+DUMMY1/LJ036-0174.wav|ðɪs ɪz ðɪ ɐpɹˈɑːksɪmət tˈaɪm hiː ˈɛntɚd ðə ɹˈuːmɪŋhˌaʊs, ɐkˈoːɹdɪŋ tʊ ˈɜːliːn ɹˈɑːbɚts, ðə hˈaʊskiːpɚ ðˈɛɹ.
+DUMMY1/LJ046-0146.wav|ðə kɹaɪtˈiəɹɪə ɪn ɪfˈɛkt pɹˈaɪɚ tə noʊvˈɛmbɚ twˈɛntitˈuː, naɪntˈiːn sˈɪkstiθɹˈiː, fɔːɹ dɪtˈɜːmɪnɪŋ wˈɛðɚ tʊ ɐksˈɛpt mətˈiəɹɪəl fɚðə pˌiːˌɑːɹˈɛs dʒˈɛnɚɹəl fˈaɪlz
+DUMMY1/LJ017-0044.wav|ænd ðə dˈiːpəst æŋzˈaɪəɾi wʌz fˈɛlt ðætðə kɹˈaɪm, ɪf kɹˈaɪm ðˈɛɹ hɐdbɪn, ʃˌʊd biː bɹˈɔːt hˈoʊm tʊ ɪts pˈɜːpɪtɹˌeɪɾɚ.
+DUMMY1/LJ017-0070.wav|bˌʌt hɪz spˈoːɹɾɪŋ ˌɑːpɚɹˈeɪʃənz dɪdnˌɑːt pɹˈɑːspɚ, ænd hiː bɪkˌeɪm ɐ nˈiːdi mˈæn, ˈɔːlweɪz dɹˈɪvən tə dˈɛspɚɹət stɹˈeɪts fɔːɹ kˈæʃ.
+DUMMY1/LJ014-0020.wav|hiː wʌz sˈuːn ˈæftɚwɚdz ɐɹˈɛstᵻd ˌɑːn səspˈɪʃən, ænd ɐ sˈɜːtʃ ʌv hɪz lˈɑːdʒɪŋz bɹˈɔːt tə lˈaɪt sˈɛvɹəl ɡˈɑːɹmənts sˈætʃɚɹˌeɪɾᵻd wɪð blˈʌd;
+DUMMY1/LJ016-0020.wav|hiː nˈɛvɚ ɹˈiːtʃt ðə sˈɪstɚn, bˌʌt fˈɛl bˈæk ˌɪntʊ ðə jˈɑːɹd, ˈɪndʒɚɹɪŋ hɪz lˈɛɡz sɪvˈɪɹli.
+DUMMY1/LJ045-0230.wav|wˌɛn hiː wʌz fˈaɪnəli ˌæpɹɪhˈɛndᵻd ɪnðə tˈɛksəs θˈiəɾɚ. ɑːlðˈoʊ ɪt ɪz nˌɑːt fˈʊli kɚɹˈɑːbɚɹˌeɪɾᵻd baɪ ˈʌðɚz hˌuː wɜː pɹˈɛzənt,
+DUMMY1/LJ035-0129.wav|ænd ʃiː mˈʌstɐv ɹˈʌn dˌaʊn ðə stˈɛɹz ɐhˈɛd ʌv ˈɑːswəld ænd wʊd pɹˈɑːbəbli hæv sˈiːn ɔːɹ hˈɜːd hˌɪm.
+DUMMY1/LJ008-0307.wav|ˈæftɚwɚdz ɛkspɹˈɛs ɐ wˈɪʃ tə mˈɜːdɚ ðə ɹɪkˈoːɹdɚ fɔːɹ hˌævɪŋ kˈɛpt ðˌɛm sˌoʊ lˈɑːŋ ɪn səspˈɛns.
+DUMMY1/LJ008-0294.wav|nˌɪɹli ɪndˈɛfɪnətli dɪfˈɜːd.
+DUMMY1/LJ047-0148.wav|ˌɑːn ɑːktˈoʊbɚ twˈɛntifˈaɪv,
+DUMMY1/LJ008-0111.wav|ðeɪ ˈɛntɚd ˈeɪ "stˈoʊn kˈoʊld ɹˈuːm," ænd wɜː pɹˈɛzəntli dʒˈɔɪnd baɪ ðə pɹˈɪzənɚ.
+DUMMY1/LJ034-0042.wav|ðæt hiː kʊd ˈoʊnli tˈɛstɪfˌaɪ wɪð sˈɜːtənti ðætðə pɹˈɪnt wʌz lˈɛs ðɐn θɹˈiː dˈeɪz ˈoʊld.
+DUMMY1/LJ037-0234.wav|mɪsˈɛs mˈɛɹi bɹˈɑːk, ðə wˈaɪf əvə mɪkˈænɪk hˌuː wˈɜːkt æt ðə stˈeɪʃən, wʌz ðɛɹ æt ðə tˈaɪm ænd ʃiː sˈɔː ɐ wˈaɪt mˈeɪl,
+DUMMY1/LJ040-0002.wav|tʃˈæptɚ sˈɛvən. lˈiː hˈɑːɹvi ˈɑːswəld: bˈækɡɹaʊnd ænd pˈɑːsəbəl mˈoʊɾɪvz, pˈɑːɹt wˌʌn.
+DUMMY1/LJ045-0140.wav|ðɪ ˈɑːɹɡjuːmənts hiː jˈuːzd tə dʒˈʌstɪfˌaɪ hɪz jˈuːs ʌvðɪ ˈeɪliəs sədʒˈɛst ðæt ˈɑːswəld mˌeɪhɐv kˈʌm tə θˈɪŋk ðætðə hˈoʊl wˈɜːld wʌz bɪkˈʌmɪŋ ɪnvˈɑːlvd
+DUMMY1/LJ012-0035.wav|ðə nˈʌmbɚ ænd nˈeɪmz ˌɑːn wˈɑːtʃᵻz, wɜː kˈɛɹfəli ɹɪmˈuːvd ɔːɹ əblˈɪɾɚɹˌeɪɾᵻd ˈæftɚ ðə ɡˈʊdz pˈæst ˌaʊɾəv hɪz hˈændz.
+DUMMY1/LJ012-0250.wav|ɑːnðə sˈɛvənθ dʒuːlˈaɪ, eɪtˈiːn θˈɜːɾisˈɛvən,
+DUMMY1/LJ016-0179.wav|kəntɹˈæktᵻd wɪð ʃˈɛɹɪfs ænd kənvˈɛnɚz tə wˈɜːk baɪ ðə dʒˈɑːb.
+DUMMY1/LJ016-0138.wav|æɾə dˈɪstəns fɹʌmðə pɹˈɪzən.
+DUMMY1/LJ027-0052.wav|ðiːz pɹˈɪnsɪpəlz ʌv həmˈɑːlədʒi ɑːɹ ɪsˈɛnʃəl tʊ ɐ kɚɹˈɛkt ɪntˌɜːpɹɪtˈeɪʃən ʌvðə fˈækts ʌv mɔːɹfˈɑːlədʒi.
+DUMMY1/LJ031-0134.wav|ˌɑːn wˈʌn əkˈeɪʒən mɪsˈɛs dʒˈɑːnsən, ɐkˈʌmpənɪd baɪ tˈuː sˈiːkɹət sˈɜːvɪs ˈeɪdʒənts, lˈɛft ðə ɹˈuːm tə sˈiː mɪsˈɛs kˈɛnədi ænd mɪsˈɛs kənˈæli.
+DUMMY1/LJ019-0273.wav|wˌɪtʃ sˌɜː dʒˈɑːʃjuːə dʒˈɛb tˈoʊld ðə kəmˈɪɾi hiː kənsˈɪdɚd ðə pɹˈɑːpɚɹ ˈɛlɪmənts ʌv pˈiːnəl dˈɪsɪplˌɪn.
+DUMMY1/LJ014-0110.wav|æt ðə fˈɜːst ðə bˈɑːksᵻz wɜːɹ ɪmpˈaʊndᵻd, ˈoʊpənd, ænd fˈaʊnd tə kəntˈeɪn mˈɛnɪəv oʊkˈɑːnɚz ɪfˈɛkts.
+DUMMY1/LJ034-0160.wav|ˌɑːn bɹˈɛnənz sˈʌbsɪkwənt sˈɜːtən aɪdˈɛntɪfɪkˈeɪʃən ʌv lˈiː hˈɑːɹvi ˈɑːswəld æz ðə mˈæn hiː sˈɔː fˈaɪɚ ðə ɹˈaɪfəl.
+DUMMY1/LJ038-0199.wav|ɪlˈɛvən. ɪf ˈaɪ æm ɐlˈaɪv ænd tˈeɪkən pɹˈɪzənɚ,
+DUMMY1/LJ014-0010.wav|jˈɛt hiː kʊd nˌɑːt ˌoʊvɚkˈʌm ðə stɹˈeɪndʒ fˌæsᵻnˈeɪʃən ɪt hˈɐd fɔːɹ hˌɪm, ænd ɹɪmˈeɪnd baɪ ðə sˈaɪd ʌvðə kˈɔːɹps tˈɪl ðə stɹˈɛtʃɚ kˈeɪm.
+DUMMY1/LJ033-0047.wav|ˈaɪ nˈoʊɾɪsd wɛn ˈaɪ wɛnt ˈaʊt ðætðə lˈaɪt wʌz ˈɑːn, ˈɛnd kwˈoʊt,
+DUMMY1/LJ040-0027.wav|hiː wʌz nˈɛvɚ sˈæɾɪsfˌaɪd wɪð ˈɛnɪθˌɪŋ.
+DUMMY1/LJ048-0228.wav|ænd ˈʌðɚz hˌuː wɜː pɹˈɛzənt sˈeɪ ðæt nˈoʊ ˈeɪdʒənt wʌz ɪnˈiːbɹɪˌeɪɾᵻd ɔːɹ ˈæktᵻd ɪmpɹˈɑːpɚli.
+DUMMY1/LJ003-0111.wav|hiː wʌz ɪn kˈɑːnsɪkwəns pˌʊt ˌaʊɾəv ðə pɹətˈɛkʃən ʌv ðɛɹ ɪntˈɜːnəl lˈɔː, ˈɛnd kwˈoʊt. ðɛɹ kˈoʊd wʌzɐ sˈʌbdʒɛkt ʌv sˌʌm kjˌʊɹɪˈɑːsɪɾi.
+DUMMY1/LJ008-0258.wav|lˈɛt mˌiː ɹɪtɹˈeɪs maɪ stˈɛps, ænd spˈiːk mˈoːɹ ɪn diːtˈeɪl ʌvðə tɹˈiːtmənt ʌvðə kəndˈɛmd ɪn ðoʊz blˈʌdθɜːsti ænd bɹˈuːɾəli ɪndˈɪfɹənt dˈeɪz,
+DUMMY1/LJ029-0022.wav|ðɪ ɚɹˈɪdʒɪnəl plˈæn kˈɔːld fɚðə pɹˈɛzɪdənt tə spˈɛnd ˈoʊnli wˈʌn dˈeɪ ɪnðə stˈeɪt, mˌeɪkɪŋ wˈɜːlwɪnd vˈɪzɪts tə dˈæləs, fˈɔːɹt wˈɜːθ, sˌæn æntˈoʊnɪˌoʊ, ænd hjˈuːstən.
+DUMMY1/LJ004-0045.wav|mˈɪstɚ stˈɜːdʒᵻz bˈoːɹn, sˌɜː dʒˈeɪmz mˈækɪntˌɑːʃ, sˌɜː dʒˈeɪmz skˈɑːɹlɪt, ænd wˈɪljəm wˈɪlbɚfˌoːɹs.

filelists/vctk_audio_sid_text_test_filelist.txt

+DUMMY2/p229/p229_128.wav|67|The whole process is a vicious circle at the moment.
+DUMMY2/p234/p234_112.wav|3|That would be a serious problem.
+DUMMY2/p298/p298_125.wav|68|I asked why he had come.
+DUMMY2/p283/p283_318.wav|95|If not, he should go home.
+DUMMY2/p260/p260_046.wav|81|It is marvellous.
+DUMMY2/p281/p281_306.wav|36|These figures are truly awful.
+DUMMY2/p285/p285_247.wav|2|Now, suddenly, we have this new landscape.
+DUMMY2/p237/p237_180.wav|61|A helpline number is published at the end of this article.
+DUMMY2/p259/p259_052.wav|7|Maybe full-time referees will provide the answer.)
+DUMMY2/p314/p314_053.wav|51|Rangers deserved to beat us.
+DUMMY2/p345/p345_070.wav|82|I haven't made any definite decisions.
+DUMMY2/p269/p269_132.wav|94|Who will attend?
+DUMMY2/p347/p347_295.wav|46|It is typical of me.
+DUMMY2/p251/p251_223.wav|9|For the refugees, the return will not come a moment too soon.
+DUMMY2/p300/p300_224.wav|102|There is nothing like this back home.
+DUMMY2/p276/p276_076.wav|106|He confirmed that the document was valid.
+DUMMY2/p294/p294_271.wav|104|I also thought, This is a feature film.
+DUMMY2/p259/p259_257.wav|7|The amount of alcohol as a whole was very high.)
+DUMMY2/p248/p248_131.wav|99|The whole thing of doing the movie was a risk.
+DUMMY2/p334/p334_023.wav|38|If the red of the second bow falls upon the green of the first, the result is to give a bow with an abnormally wide yellow band, since red and green light when mixed form yellow.
+DUMMY2/p345/p345_386.wav|82|It is quite simple.
+DUMMY2/p330/p330_382.wav|1|Neither was involved in violence.
+DUMMY2/p246/p246_133.wav|5|My daughter is an adult.
+DUMMY2/p257/p257_140.wav|105|It's not true.
+DUMMY2/p340/p340_011.wav|74|When a man looks for something beyond his reach, his friends say he is looking for the pot of gold at the end of the rainbow.
+DUMMY2/p284/p284_409.wav|16|Then , he laughs.
+DUMMY2/p317/p317_129.wav|97|You would be wrong.
+DUMMY2/p279/p279_183.wav|25|Government will intervene.
+DUMMY2/p376/p376_273.wav|71|"If not, he should go home."
+DUMMY2/p233/p233_109.wav|84|It is not affected by the sale.
+DUMMY2/p234/p234_118.wav|3|When we looked at the company.
+DUMMY2/p336/p336_207.wav|98|The train was on time.
+DUMMY2/p227/p227_213.wav|29|What are you not good at ?
+DUMMY2/p347/p347_113.wav|46|They are all Arabs.
+DUMMY2/p317/p317_125.wav|97|Alan Milburn, the health secretary, refused to comment.
+DUMMY2/p341/p341_031.wav|66|I was left-handed, but it was just a matter of practice.
+DUMMY2/p244/p244_338.wav|78|This isn't a betrayal of public services, it's their renewal.
+DUMMY2/p250/p250_288.wav|24|Is it in the right place ?
+DUMMY2/p233/p233_156.wav|84|It opens the door to the Champions League.
+DUMMY2/p334/p334_118.wav|38|The sanctions are about collective punishment.
+DUMMY2/p258/p258_027.wav|26|People come into the Borders for the beauty of the background.
+DUMMY2/p341/p341_187.wav|66|His signature is his handwriting.
+DUMMY2/p258/p258_347.wav|26|The composer will conduct.
+DUMMY2/p262/p262_005.wav|45|She can scoop these things into three red bags, and we will go meet her Wednesday at the train station.
+DUMMY2/p231/p231_174.wav|50|One season, they might do well.
+DUMMY2/p363/p363_285.wav|6|But he was far from alone.
+DUMMY2/p303/p303_113.wav|44|Winning, meanwhile, is headed back to New York City.
+DUMMY2/p274/p274_181.wav|32|Is it in the right place ?)
+DUMMY2/p297/p297_023.wav|42|If the red of the second bow falls upon the green of the first, the result is to give a bow with an abnormally wide yellow band, since red and green light when mixed form yellow.
+DUMMY2/p247/p247_065.wav|14|We will pay their bills.)
+DUMMY2/p273/p273_105.wav|56|The pressure is on them.
+DUMMY2/p245/p245_167.wav|59|It was an odd affair, in many respects.
+DUMMY2/p364/p364_239.wav|88|It was a long time coming.
+DUMMY2/p263/p263_047.wav|39|The Yugoslav president said he did not recognise the election outcome.
+DUMMY2/p283/p283_333.wav|95|No final decision has been taken.
+DUMMY2/p335/p335_313.wav|49|The issues are very intense.
+DUMMY2/p280/p280_172.wav|52|He said some things which were better left alone.
+DUMMY2/p266/p266_006.wav|20|When the sunlight strikes raindrops in the air, they act as a prism and form a rainbow.
+DUMMY2/p260/p260_027.wav|81|Is this accurate?
+DUMMY2/p326/p326_214.wav|28|It's not long enough.
+DUMMY2/p259/p259_253.wav|7|You are like an animal.)
+DUMMY2/p228/p228_109.wav|57|However, the intensive care unit at the Southern General Hospital was full.
+DUMMY2/p376/p376_228.wav|71|"Half of young people had had contact with the police."
+DUMMY2/p361/p361_057.wav|79|That was something else.
+DUMMY2/p341/p341_058.wav|66|Labour accused the Tory leader of panicking.
+DUMMY2/p363/p363_247.wav|6|We are taking no chances this time.
+DUMMY2/p262/p262_054.wav|45|Already, he has been a tremendous influence in the dressing room.
+DUMMY2/p238/p238_090.wav|37|He thought she was amazing.
+DUMMY2/p306/p306_020.wav|12|Many complicated ideas about the rainbow have been formed.
+DUMMY2/p238/p238_339.wav|37|Harry Potter has lost his magic.
+DUMMY2/p302/p302_285.wav|30|Others said they had been beaten by police.
+DUMMY2/p275/p275_377.wav|40|Family liaison officers are now working to support the family.
+DUMMY2/p267/p267_286.wav|0|And they were being paid ?
+DUMMY2/p243/p243_090.wav|53|Among them was Gary Robertson from Dundee.
+DUMMY2/p274/p274_213.wav|32|It's easy to be negative about these things.)
+DUMMY2/p286/p286_310.wav|63|But it has been an amazing experience.
+DUMMY2/p294/p294_293.wav|104|That case has still not been settled.
+DUMMY2/p273/p273_174.wav|56|Two years later, she was dead.
+DUMMY2/p231/p231_408.wav|50|I should think so, too.
+DUMMY2/p323/p323_084.wav|34|And, within itself, it is visionary.
+DUMMY2/p248/p248_025.wav|99|She is given a new deputy minister for transport and planning.
+DUMMY2/p288/p288_197.wav|47|They are in the euro.
+DUMMY2/p300/p300_029.wav|102|Of course, this is nice to hear.
+DUMMY2/p299/p299_344.wav|58|He will never walk the streets again.
+DUMMY2/p376/p376_168.wav|71|"They will do their own thing."
+DUMMY2/p275/p275_277.wav|40|He looked very sharp.
+DUMMY2/p312/p312_022.wav|62|The actual primary rainbow observed is said to be the effect of super-imposition of a number of bows.
+DUMMY2/p278/p278_093.wav|10|It was some time before she found out he was safe.
+DUMMY2/p302/p302_312.wav|30|However, there was no hope, and glory too, for Scotland.
+DUMMY2/p236/p236_368.wav|75|It was like a weekly wage.
+DUMMY2/p237/p237_056.wav|61|No-one has appeared in court in relation to her death.
+DUMMY2/p305/p305_162.wav|54|For starters, many of the Scotland team didn't turn up.
+DUMMY2/p275/p275_018.wav|40|Aristotle thought that the rainbow was caused by reflection of the sun's rays by the rain.
+DUMMY2/p310/p310_039.wav|17|But one shouldn't go by that.
+DUMMY2/p299/p299_310.wav|58|Farmers have been an endangered species.
+DUMMY2/p259/p259_428.wav|7|In general terms, the proposals are very much in line with expectations.)
+DUMMY2/p339/p339_155.wav|18|It is just a matter of time.
+DUMMY2/p229/p229_347.wav|67|I've got no secret.
+DUMMY2/p256/p256_308.wav|90|Let's hope it's an investment in the future.
+DUMMY2/p360/p360_204.wav|60|It is dangerous and it is a lie.
+DUMMY2/p238/p238_208.wav|37|The refund is fully justified.
+DUMMY2/p341/p341_319.wav|66|This is very bad news.
+DUMMY2/p336/p336_399.wav|98|The pressure is enormous.
+DUMMY2/p229/p229_067.wav|67|That was the easy election.
+DUMMY2/p329/p329_159.wav|103|No-one, not even the Scottish Arts Council, was interested in her.
+DUMMY2/p258/p258_304.wav|26|The confidence is low, but it is a difficult thing to understand.
+DUMMY2/p312/p312_033.wav|62|Haven't been so lucky since.
+DUMMY2/p266/p266_093.wav|20|Two other men, including the taxi driver, were wounded in the attack.
+DUMMY2/p307/p307_396.wav|22|It was early morning.
+DUMMY2/p326/p326_039.wav|28|There is nothing like this back home.
+DUMMY2/p333/p333_009.wav|64|There is , according to legend, a boiling pot of gold at one end.
+DUMMY2/p295/p295_154.wav|92|I remember it clearly.
+DUMMY2/p297/p297_007.wav|42|The rainbow is a division of white light into many beautiful colors.
+DUMMY2/p233/p233_153.wav|84|It would be a last resort.
+DUMMY2/p244/p244_220.wav|78|This year, it will amount to a few hundred thousand pounds.
+DUMMY2/p267/p267_136.wav|0|It has become a way of life.
+DUMMY2/p311/p311_313.wav|4|The decision was left entirely to him.
+DUMMY2/p230/p230_113.wav|35|You can spend money on housing.
+DUMMY2/p318/p318_295.wav|19|We gave them the goal.
+DUMMY2/p236/p236_090.wav|75|After the match, do you ?
+DUMMY2/p364/p364_156.wav|88|Ferguson had done his homework.
+DUMMY2/p310/p310_260.wav|17|That is my role.
+DUMMY2/p323/p323_261.wav|34|They hoped to remain in the Edinburgh area.
+DUMMY2/p284/p284_393.wav|16|On the contrary, it was actually very funny.
+DUMMY2/p276/p276_460.wav|106|We will pay their bills.
+DUMMY2/p363/p363_273.wav|6|The plot is minimal.
+DUMMY2/p250/p250_039.wav|24|Costs have got to be controlled.
+DUMMY2/p317/p317_244.wav|97|This event allows us to emphasise the positive.
+DUMMY2/p280/p280_042.wav|52|He does not even trust his own members.
+DUMMY2/p227/p227_342.wav|29|Have a look at this lot.
+DUMMY2/p333/p333_255.wav|64|But the Foreign Secretary can cope.
+DUMMY2/p232/p232_103.wav|96|We recognise the important role of golf in attracting visitors.
+DUMMY2/p305/p305_138.wav|54|Another suggested the company should carry only pedestrians.
+DUMMY2/p248/p248_196.wav|99|It is not satisfied with the standard of fire safety provisions.
+DUMMY2/p230/p230_166.wav|35|We believe in the medium term.
+DUMMY2/p303/p303_275.wav|44|There are lots of these women in Finland.
+DUMMY2/p280/p280_208.wav|52|Gas production was also at record levels last year.
+DUMMY2/p330/p330_252.wav|1|I first met him last summer.
+DUMMY2/p330/p330_209.wav|1|I will not take you out of context.
+DUMMY2/p240/p240_214.wav|93|It had all been arranged.
+DUMMY2/p293/p293_185.wav|23|This is the stuff of live music.
+DUMMY2/p237/p237_230.wav|61|Clearly, the stakes are high.
+DUMMY2/p277/p277_014.wav|89|To the Hebrews it was a token that there would be no more universal floods.
+DUMMY2/p251/p251_107.wav|9|It had been played at festivals.
+DUMMY2/p302/p302_011.wav|30|When a man looks for something beyond his reach, his friends say he's looking for the pot of gold at the end of the rainbow.
+DUMMY2/p264/p264_147.wav|65|She's been shot.)
+DUMMY2/p236/p236_288.wav|75|Brown is an interesting man, but he is not desperate.
+DUMMY2/p323/p323_297.wav|34|I've got the shirt.
+DUMMY2/p297/p297_402.wav|42|I don't have a problem with getting older.
+DUMMY2/p267/p267_182.wav|0|A team is a team.
+DUMMY2/p226/p226_121.wav|43|Maybe this battle has been.
+DUMMY2/p311/p311_226.wav|4|Gone with them is any sense of narrative.
+DUMMY2/p335/p335_279.wav|49|Or rather he did and he didn't.
+DUMMY2/p270/p270_068.wav|8|Then followed a bout of flu.
+DUMMY2/p260/p260_072.wav|81|It was magic.
+DUMMY2/p362/p362_341.wav|15|The result could be all down to turnout.
+DUMMY2/p228/p228_180.wav|57|One season, they might do well.
+DUMMY2/p316/p316_152.wav|85|Failure is not an option.
+DUMMY2/p317/p317_423.wav|97|Manchester United are the classic example.
+DUMMY2/p243/p243_292.wav|53|Its work includes dealing with child abuse.
+DUMMY2/p362/p362_054.wav|15|We certainly hope we have been successful.
+DUMMY2/p243/p243_305.wav|53|What happened in that game ?
+DUMMY2/p364/p364_297.wav|88|It was just one man.
+DUMMY2/p255/p255_049.wav|31|We were surprised to see the photograph.
+DUMMY2/p297/p297_358.wav|42|He said he had no reports of casualties.
+DUMMY2/p283/p283_430.wav|95|My aim is a top six finish.
+DUMMY2/p310/p310_300.wav|17|Mike Tyson went to prison.
+DUMMY2/p363/p363_051.wav|6|The nation has his music.
+DUMMY2/p261/p261_112.wav|100|It became a national network.
+DUMMY2/p234/p234_036.wav|3|It was sold at a loss.
+DUMMY2/p247/p247_470.wav|14|They were good years for him.)
+DUMMY2/p303/p303_269.wav|44|After that nothing could save him.
+DUMMY2/p317/p317_256.wav|97|The man was pronounced dead on arrival.
+DUMMY2/p351/p351_161.wav|33|Paterson can afford to be generous.
+DUMMY2/p314/p314_295.wav|51|You take a risk.
+DUMMY2/p293/p293_268.wav|23|Our children are our future.
+DUMMY2/p306/p306_352.wav|12|Who has the second highest?
+DUMMY2/p273/p273_098.wav|56|The following are the principal provisions.
+DUMMY2/p285/p285_029.wav|2|Their courage, and their honesty, should be respected.
+DUMMY2/p266/p266_073.wav|20|It works for us.
+DUMMY2/p374/p374_288.wav|11|I had a good life at Rangers.
+DUMMY2/p280/p280_171.wav|52|You need a long-term strategy in football.
+DUMMY2/p239/p239_203.wav|48|It is all to do with the coaching.
+DUMMY2/p287/p287_292.wav|77|In essence, the teaching profession has a choice.
+DUMMY2/p330/p330_112.wav|1|Wallace was in at the deep end.
+DUMMY2/p247/p247_141.wav|14|They made such decisions in London.)
+DUMMY2/p277/p277_050.wav|89|This represents a tough game for us.
+DUMMY2/p233/p233_289.wav|84|He looked very sharp.
+DUMMY2/p284/p284_103.wav|16|Meanwhile, the Scottish Consumer Council yesterday offered support for the new Bill.
+DUMMY2/p334/p334_366.wav|38|We will miss him very much.
+DUMMY2/p238/p238_196.wav|37|Tiger is not the norm.
+DUMMY2/p304/p304_193.wav|72|Then they were awarded a penalty.
+DUMMY2/p229/p229_348.wav|67|Look at the witnesses.
+DUMMY2/p268/p268_147.wav|87|how do you get it back ?
+DUMMY2/p293/p293_348.wav|23|He quit in October.
+DUMMY2/p341/p341_082.wav|66|John Reid, the Northern Ireland secretary, yesterday appealed for restraint.
+DUMMY2/p258/p258_097.wav|26|It is a good lifestyle.
+DUMMY2/p340/p340_220.wav|74|Not so, it seems.
+DUMMY2/p269/p269_174.wav|94|Mark Fisher was a guest of the Northern Ireland Tourist Board.
+DUMMY2/p270/p270_078.wav|8|I've had it for the exams.
+DUMMY2/p334/p334_224.wav|38|I can't blame the fans.
+DUMMY2/p307/p307_306.wav|22|We're talking about creating an attractive neighbourhood.
+DUMMY2/p361/p361_205.wav|79|Translation - we got it wrong.
+DUMMY2/p229/p229_142.wav|67|What will happen then ?
+DUMMY2/p310/p310_221.wav|17|We will look into it.
+DUMMY2/p232/p232_357.wav|96|He had played well in that central role.
+DUMMY2/p263/p263_389.wav|39|This season has been a nightmare.
+DUMMY2/p283/p283_273.wav|95|Did he trip ?
+DUMMY2/p374/p374_277.wav|11|Where do you start?
+DUMMY2/p301/p301_289.wav|91|Children are using books in a terrible condition.
+DUMMY2/p345/p345_267.wav|82|Her presence was almost everywhere.
+DUMMY2/p264/p264_226.wav|65|No partners would lose their jobs.)
+DUMMY2/p253/p253_050.wav|70|A neighbour said.
+DUMMY2/p276/p276_118.wav|106|If they liked it then I'll be happy.
+DUMMY2/p295/p295_175.wav|92|Anything that can be done, the Government will do.
+DUMMY2/p247/p247_466.wav|14|I think it's a great system.)
+DUMMY2/p301/p301_182.wav|91|I see social work as a vocation, a commitment.
+DUMMY2/p294/p294_156.wav|104|We are well insured.
+DUMMY2/p287/p287_190.wav|77|We have to recognise that he is an elusive character.
+DUMMY2/p258/p258_333.wav|26|Robert is a special talent.
+DUMMY2/p275/p275_122.wav|40|Who would have?
+DUMMY2/p231/p231_259.wav|50|It was the climax of the thing.
+DUMMY2/p330/p330_073.wav|1|Over time, with patience and precision, the terrorists will be pursued.
+DUMMY2/p277/p277_239.wav|89|I should think so, too.
+DUMMY2/p374/p374_352.wav|11|As if they ever stopped.
+DUMMY2/p244/p244_258.wav|78|If it doesn't, it doesn't.
+DUMMY2/p277/p277_194.wav|89|I would think about the end of January, the beginning of February.
+DUMMY2/p241/p241_177.wav|86|The clarity is vital.
+DUMMY2/p247/p247_275.wav|14|What form did that take ?)
+DUMMY2/p230/p230_230.wav|35|That has been the easy part.
+DUMMY2/p323/p323_015.wav|34|The Greeks used to imagine that it was a sign from the gods to foretell war or heavy rain.
+DUMMY2/p269/p269_365.wav|94|But the real problem is the closure of the export market.
+DUMMY2/p310/p310_049.wav|17|They had four children together.
+DUMMY2/p281/p281_068.wav|36|I have proved that in the past.
+DUMMY2/p343/p343_162.wav|21|Dancing was her life.
+DUMMY2/p299/p299_208.wav|58|I'm a bit annoyed.
+DUMMY2/p329/p329_292.wav|103|The methadone programme is completely out of control.
+DUMMY2/p232/p232_376.wav|96|He could make it.
+DUMMY2/p305/p305_135.wav|54|I COULD hardly keep up with Professor McKean.
+DUMMY2/p351/p351_231.wav|33|We are pursuing legal action against the government.
+DUMMY2/p265/p265_153.wav|73|Military action is the only option we have on the table today.
+DUMMY2/p323/p323_137.wav|34|Everything was a dead end.
+DUMMY2/p305/p305_176.wav|54|That has given me great confidence.
+DUMMY2/p238/p238_053.wav|37|Does it matter ?
+DUMMY2/p230/p230_195.wav|35|It is not all good news and relief for Labour, however.
+DUMMY2/p238/p238_093.wav|37|He seems to have everything.
+DUMMY2/p259/p259_323.wav|7|We feel very comfortable in this international environment.)
+DUMMY2/p285/p285_032.wav|2|This is the window.
+DUMMY2/p302/p302_208.wav|30|Which means it matters.
+DUMMY2/p231/p231_176.wav|50|This much I can tell you.
+DUMMY2/p301/p301_054.wav|91|Here he is, in effect, appointing himself a judge.
+DUMMY2/p310/p310_102.wav|17|We shall rely on human beings.
+DUMMY2/p305/p305_121.wav|54|It is a vicious circle.
+DUMMY2/p231/p231_458.wav|50|She has reached the top of her profession.
+DUMMY2/p311/p311_024.wav|4|This is a very common type of bow, one showing mainly red and yellow, with little or no green or blue.
+DUMMY2/p245/p245_248.wav|59|Is there on his hands?
+DUMMY2/p333/p333_311.wav|64|Councillor Gordon has refused to stand down.
+DUMMY2/p299/p299_007.wav|58|The rainbow is a division of white light into many beautiful colors.
+DUMMY2/p229/p229_333.wav|67|She did not attend the courtroom.
+DUMMY2/p307/p307_286.wav|22|The board would report to the Scottish Parliament.
+DUMMY2/p305/p305_414.wav|54|It is the Holiday programme with a mortgage.
+DUMMY2/p264/p264_140.wav|65|He nearly killed my son.)
+DUMMY2/p374/p374_114.wav|11|I don't think it would make any difference.
+DUMMY2/p363/p363_369.wav|6|We have been overwhelmed by the response.
+DUMMY2/p293/p293_374.wav|23|I don't think the referees are against us.
+DUMMY2/p316/p316_329.wav|85|It's a production company.
+DUMMY2/p236/p236_018.wav|75|Aristotle thought that the rainbow was caused by reflection of the sun's rays by the rain.
+DUMMY2/p234/p234_332.wav|3|But it can be done.
+DUMMY2/p277/p277_132.wav|89|No production was achieved.
+DUMMY2/p326/p326_205.wav|28|As agreed, the prime minister was driven to Westminster Hall.
+DUMMY2/p272/p272_134.wav|69|This tour is critical for New Zealand rugby.
+DUMMY2/p316/p316_125.wav|85|And now the pressure is off.
+DUMMY2/p274/p274_149.wav|32|I prefer the clarity of the existing system.)
+DUMMY2/p227/p227_368.wav|29|A crucial moment has arrived.
+DUMMY2/p334/p334_206.wav|38|We'll have to work hard today.
+DUMMY2/p339/p339_087.wav|18|I am not completely insane.
+DUMMY2/p286/p286_453.wav|63|He was said to be emotionally disturbed.
+DUMMY2/p301/p301_110.wav|91|People want to see me on the screen.
+DUMMY2/p282/p282_188.wav|83|Suddenly, the rugby world had changed.
+DUMMY2/p263/p263_147.wav|39|Losing in that manner is very hard to take.
+DUMMY2/p256/p256_253.wav|90|I was never going to play against Scotland.
+DUMMY2/p374/p374_165.wav|11|Something has got to change.
+DUMMY2/p262/p262_232.wav|45|It's very safe.
+DUMMY2/p267/p267_417.wav|0|This is no reflection on Rangers.
+DUMMY2/p240/p240_078.wav|93|I've got the shirt.
+DUMMY2/p347/p347_143.wav|46|There is no sign of anyone being hurt.
+DUMMY2/p245/p245_069.wav|59|She died in hospital two hours later.
+DUMMY2/p233/p233_172.wav|84|They say that vital evidence was not heard in court.
+DUMMY2/p280/p280_282.wav|52|Overall, the last hole was good to the women.
+DUMMY2/p298/p298_364.wav|68|I'm looking at ways to do that now.
+DUMMY2/p339/p339_240.wav|18|The teacher would have approved.
+DUMMY2/p361/p361_387.wav|79|We have been going for three years.
+DUMMY2/p278/p278_221.wav|10|January is a bad time of year.
+DUMMY2/p334/p334_289.wav|38|They married in August last year.
+DUMMY2/p250/p250_187.wav|24|This championship is different from the other majors.
+DUMMY2/p248/p248_283.wav|99|Maloney is an engaging talent.
+DUMMY2/p275/p275_261.wav|40|It will be done in stages.
+DUMMY2/p288/p288_024.wav|47|This is a very common type of bow, one showing mainly red and yellow, with little or no green or blue.
+DUMMY2/p271/p271_454.wav|27|It's a miracle.
+DUMMY2/p252/p252_408.wav|55|They had to have hospital treatment.
+DUMMY2/p261/p261_192.wav|100|It was a pre-emptive strike.
+DUMMY2/p308/p308_099.wav|107|Glasgow deserved their win, but we made them look good.
+DUMMY2/p288/p288_070.wav|47|Neither it is.
+DUMMY2/p317/p317_356.wav|97|We're not an employment agency.
+DUMMY2/p351/p351_251.wav|33|That is a matter for the Scottish Parliament.
+DUMMY2/p329/p329_075.wav|103|This will be no easy option.
+DUMMY2/p261/p261_180.wav|100|I've been in two finals, and I've got a medal.
+DUMMY2/p301/p301_272.wav|91|Drink and petrol prices remain untouched.
+DUMMY2/p277/p277_404.wav|89|Whether the High Court will interfere with the sentence is another matter.
+DUMMY2/p301/p301_135.wav|91|How good is Lennox Lewis?
+DUMMY2/p246/p246_333.wav|5|Two people were interviewed.
+DUMMY2/p340/p340_250.wav|74|The film was great.
+DUMMY2/p268/p268_355.wav|87|They had declined in each of the two preceding quarters.
+DUMMY2/p236/p236_143.wav|75|The whole industry is a shambles.
+DUMMY2/p231/p231_398.wav|50|They have failed to deliver.
+DUMMY2/p340/p340_322.wav|74|I am extremely cautious.
+DUMMY2/p228/p228_048.wav|57|The Scottish Parliament is also looking at similar measures.
+DUMMY2/p334/p334_193.wav|38|It is in our own hands.
+DUMMY2/p226/p226_128.wav|43|I felt very strongly that England should have it.
+DUMMY2/p279/p279_064.wav|25|We have not given up hope.
+DUMMY2/p304/p304_416.wav|72|He took over our lives.
+DUMMY2/p313/p313_119.wav|76|O Neill is reputed to have replied.
+DUMMY2/p287/p287_195.wav|77|It comes from reflection or thinking.
+DUMMY2/p234/p234_008.wav|3|These take the shape of a long round arch, with its path high above, and its two ends apparently beyond the horizon.
+DUMMY2/p277/p277_119.wav|89|Naturally, it was not difficult to find support for these proposals.
+DUMMY2/p281/p281_394.wav|36|What are they for ?
+DUMMY2/p287/p287_272.wav|77|And they were being paid ?
+DUMMY2/p288/p288_071.wav|47|He seemed to lose his focus.
+DUMMY2/p335/p335_245.wav|49|A friendship that will endure.
+DUMMY2/p239/p239_061.wav|48|All manner of precaution and protection are taken.
+DUMMY2/p254/p254_003.wav|41|Six spoons of fresh snow peas, five thick slabs of blue cheese, and maybe a snack for her brother Bob.
+DUMMY2/p259/p259_282.wav|7|Washington is consumed by the crisis.)
+DUMMY2/p253/p253_202.wav|70|Sadly, it can't.
+DUMMY2/p318/p318_333.wav|19|But when we do it is great.
+DUMMY2/p351/p351_363.wav|33|You will never forget the clutching horror.
+DUMMY2/p241/p241_374.wav|86|There is no signature.
+DUMMY2/p272/p272_216.wav|69|The report is due out next month.
+DUMMY2/p330/p330_355.wav|1|I've got my own ideas.
+DUMMY2/p270/p270_179.wav|8|The outcome is now in our own hands.
+DUMMY2/p257/p257_079.wav|105|It is not long term, but I need time to recover.
+DUMMY2/p257/p257_027.wav|105|They should have a major rethink about the event for next year.
+DUMMY2/p279/p279_118.wav|25|Does this mean.
+DUMMY2/p334/p334_058.wav|38|Hopefully, it will be built by next year.
+DUMMY2/p363/p363_178.wav|6|That was a huge experience.
+DUMMY2/p376/p376_227.wav|71|"And thought we would get away with it."
+DUMMY2/p330/p330_411.wav|1|You know, he was struggling with his game all week.
+DUMMY2/p326/p326_316.wav|28|It certainly sounded it at times.
+DUMMY2/p323/p323_048.wav|34|Mackie was at home, unable to watch.
+DUMMY2/p313/p313_422.wav|76|Now, that is a good deal.
+DUMMY2/p364/p364_113.wav|88|It was just great.
+DUMMY2/p286/p286_414.wav|63|It's just a training thing.
+DUMMY2/p288/p288_229.wav|47|However, no further action was taken by police.
+DUMMY2/p259/p259_142.wav|7|What happened in that game ?)
+DUMMY2/p297/p297_118.wav|42|It's too big a risk to take.
+DUMMY2/p313/p313_209.wav|76|The night is young.
+DUMMY2/p303/p303_279.wav|44|I bought a car at auction.
+DUMMY2/p345/p345_166.wav|82|Miller was every bit as happy.
+DUMMY2/p333/p333_289.wav|64|It's going to be quite a challenge.
+DUMMY2/p336/p336_323.wav|98|One paper was not returned.
+DUMMY2/p271/p271_082.wav|27|He is in the queue.
+DUMMY2/p314/p314_175.wav|51|There is no substitute.
+DUMMY2/p248/p248_124.wav|99|I can't even get into the A team.
+DUMMY2/p297/p297_160.wav|42|Tax is a matter for national governments.
+DUMMY2/p236/p236_299.wav|75|how do you get it back ?
+DUMMY2/p248/p248_300.wav|99|It wasn't just the character and energy of the playing.
+DUMMY2/p231/p231_429.wav|50|He is on the wrong side.
+DUMMY2/p250/p250_368.wav|24|We put our bid in last night.
+DUMMY2/p376/p376_191.wav|71|"I am totally surprised."
+DUMMY2/p250/p250_419.wav|24|She started to put on weight.
+DUMMY2/p239/p239_037.wav|48|He works at the airport.
+DUMMY2/p340/p340_165.wav|74|He was very fit.
+DUMMY2/p339/p339_258.wav|18|There are not too many like him.
+DUMMY2/p326/p326_266.wav|28|It may also be her last.
+DUMMY2/p231/p231_472.wav|50|He felt it was the right time.
+DUMMY2/p261/p261_411.wav|100|I had a fortunate war.
+DUMMY2/p272/p272_359.wav|69|Now, though, he has an incentive.
+DUMMY2/p340/p340_015.wav|74|The Greeks used to imagine that it was a sign from the gods to foretell war or heavy rain.
+DUMMY2/p283/p283_022.wav|95|The actual primary rainbow observed is said to be the effect of super-imposition of a number of bows.
+DUMMY2/p281/p281_334.wav|36|However, the groups denied the claims.
+DUMMY2/p318/p318_223.wav|19|We remain committed to it, as does the government.
+DUMMY2/p281/p281_039.wav|36|This film will be totally awesome.
+DUMMY2/p270/p270_013.wav|8|Some have accepted it as a miracle without physical explanation.
+DUMMY2/p243/p243_047.wav|53|However, there is an issue, isn't there ?
+DUMMY2/p374/p374_122.wav|11|The course is in great condition.
+DUMMY2/p302/p302_040.wav|30|On fuel, the Chancellor has a number of options.
+DUMMY2/p254/p254_231.wav|41|And thought we would get away with it.
+DUMMY2/p246/p246_222.wav|5|It's not before time.
+DUMMY2/p262/p262_044.wav|45|It is difficult for Ali.
+DUMMY2/p270/p270_005.wav|8|She can scoop these things into three red bags, and we will go meet her Wednesday at the train station.
+DUMMY2/p274/p274_340.wav|32|This is a historic occasion.)
+DUMMY2/p329/p329_045.wav|103|I hope you will leave it at that.
+DUMMY2/p285/p285_188.wav|2|Any change would be subject to the Scottish Parliament's approval.
+DUMMY2/p260/p260_193.wav|81|The Shadow Chancellor is away on holiday.
+DUMMY2/p259/p259_371.wav|7|He was unable to come.)
+DUMMY2/p275/p275_052.wav|40|Several other pupils and staff were seriously injured in the accident.
+DUMMY2/p233/p233_159.wav|84|But he stressed that the partnership is not a construction company.
+DUMMY2/p277/p277_312.wav|89|It will work.
+DUMMY2/p295/p295_211.wav|92|Leaving the Labour Party is one thing.
+DUMMY2/p297/p297_150.wav|42|It is the wealthiest in Europe.
+DUMMY2/p305/p305_026.wav|54|He added, however, that all options are under review.
+DUMMY2/p292/p292_121.wav|13|This would not be my first choice.
+DUMMY2/p253/p253_346.wav|70|It is the Holiday programme with a mortgage.
+DUMMY2/p363/p363_171.wav|6|He didn't know where to look.
+DUMMY2/p233/p233_128.wav|84|It is still too early for any likely contenders to have emerged.
+DUMMY2/p251/p251_137.wav|9|We are currently consulting with a wide range of interested parties.
+DUMMY2/p334/p334_034.wav|38|Appointed general secretary last September.
+DUMMY2/p286/p286_225.wav|63|This will take several weeks.
+DUMMY2/p363/p363_183.wav|6|Public safety is paramount.
+DUMMY2/p256/p256_207.wav|90|After that time, the market itself will set the prices.
+DUMMY2/p273/p273_311.wav|56|Job losses were also announced.
+DUMMY2/p274/p274_425.wav|32|The projections are very positive for South Africa.)
+DUMMY2/p254/p254_065.wav|41|That's the day job.
+DUMMY2/p335/p335_123.wav|49|Wagner was never like this.
+DUMMY2/p258/p258_105.wav|26|We do not expect any surplus.
+DUMMY2/p286/p286_294.wav|63|It was an easy decision to come here.
+DUMMY2/p361/p361_218.wav|79|But we were wrong.
+DUMMY2/p247/p247_426.wav|14|Being captain of this club is fantastic.)
+DUMMY2/p266/p266_391.wav|20|In time, may prove a worthy successor to Billy Dodds.
+DUMMY2/p253/p253_116.wav|70|It is so sad.
+DUMMY2/p261/p261_081.wav|100|Our mother is very worried.
+DUMMY2/p268/p268_131.wav|87|But then they scored their fourth.
+DUMMY2/p229/p229_192.wav|67|I have the first six months of next season to prove myself.
+DUMMY2/p275/p275_260.wav|40|They want to shut the Scottish Office.
+DUMMY2/p313/p313_109.wav|76|Nothing is being offered in exchange.
+DUMMY2/p347/p347_072.wav|46|Thankfully, Mr Campbell was able to help.
+DUMMY2/p298/p298_334.wav|68|Hopefully, the whole of Scottish rugby was paying attention.
+DUMMY2/p271/p271_232.wav|27|Jim Wallace, the justice minister, acknowledged that prisoner numbers were a concern.
+DUMMY2/p283/p283_056.wav|95|For the meantime, though, the signs are good.
+DUMMY2/p255/p255_239.wav|31|It's the same as Glasgow.
+DUMMY2/p267/p267_244.wav|0|We have come a long way in the last few sessions.
+DUMMY2/p340/p340_403.wav|74|I had a ball today.
+DUMMY2/p230/p230_083.wav|35|It might change your life.
+DUMMY2/p299/p299_403.wav|58|We will have to see, but it makes you think.
+DUMMY2/p343/p343_128.wav|21|Then came the crunch.
+DUMMY2/p297/p297_021.wav|42|The difference in the rainbow depends considerably upon the size of the drops, and the width of the colored band increases as the size of the drops increases.
+DUMMY2/p298/p298_275.wav|68|There are lots of these women in Finland.
+DUMMY2/p347/p347_286.wav|46|It is just too long since the war.
+DUMMY2/p239/p239_445.wav|48|Either group is living in fantasy land.
+DUMMY2/p286/p286_003.wav|63|Six spoons of fresh snow peas, five thick slabs of blue cheese, and maybe a snack for her brother Bob.
+DUMMY2/p299/p299_082.wav|58|I still feel like a wee boy.
+DUMMY2/p306/p306_213.wav|12|It is like being a qualifier again.
+DUMMY2/p339/p339_305.wav|18|We know the goals will come.
+DUMMY2/p265/p265_274.wav|73|This time, for Rangers, it is certainly the latter.
+DUMMY2/p310/p310_382.wav|17|It has the Bank of Scotland behind it.
+DUMMY2/p335/p335_403.wav|49|Anyway, even if they didn't it wouldn't have mattered.
+DUMMY2/p246/p246_330.wav|5|I would be quite happy for the money to be given back.
+DUMMY2/p288/p288_386.wav|47|There is a solution, she believes.
+DUMMY2/p234/p234_019.wav|3|Since then physicists have found that it is not reflection, but refraction by the raindrops which causes the rainbows.
+DUMMY2/p287/p287_408.wav|77|FIRST, we had the Battle of Britain.
+DUMMY2/p286/p286_249.wav|63|She will attend in July.
+DUMMY2/p251/p251_235.wav|9|I'd never seen a play about me.
+DUMMY2/p347/p347_291.wav|46|Insurance will be covered by the receiving galleries.
+DUMMY2/p257/p257_058.wav|105|It is not great art.
+DUMMY2/p231/p231_471.wav|50|Dennis was not so sure.
+DUMMY2/p341/p341_107.wav|66|There was great support all round the route.
+DUMMY2/p264/p264_160.wav|65|It was clearly not a battle.)
+DUMMY2/p252/p252_155.wav|55|I think, therefore I am ?
+DUMMY2/p336/p336_264.wav|98|Ferguson must take the blame.
+DUMMY2/p274/p274_142.wav|32|The referee faces a massive job.)
+DUMMY2/p303/p303_005.wav|44|She can scoop these things into three red bags, and we will go meet her Wednesday at the train station.
+DUMMY2/p233/p233_240.wav|84|The singer is expected to be in hospital for several days.
+DUMMY2/p333/p333_220.wav|64|This process of attrition is expected to continue.
+DUMMY2/p285/p285_303.wav|2|Alex Smith has been a massive influence on my career as well.
+DUMMY2/p277/p277_348.wav|89|To do so he reckons that a good opening result is essential.
+DUMMY2/p311/p311_290.wav|4|I am not in denial.
+DUMMY2/p286/p286_316.wav|63|I am a retailer by nature.
+DUMMY2/p306/p306_119.wav|12|Completion is expected by October the following year.
+DUMMY2/p240/p240_028.wav|93|Is this accurate?
+DUMMY2/p238/p238_295.wav|37|It has been recorded twice.
+DUMMY2/p278/p278_049.wav|10|He will need that machine.
+DUMMY2/p351/p351_282.wav|33|We just wish they had done so before.
+DUMMY2/p267/p267_348.wav|0|Many of these properties are located in the south of England.
+DUMMY2/p312/p312_360.wav|62|And Scotland is no different.
+DUMMY2/p311/p311_324.wav|4|He pretended not to care.
+DUMMY2/p283/p283_389.wav|95|Scrutiny by the European Parliament is limited.
+DUMMY2/p266/p266_079.wav|20|He is in the queue.
+DUMMY2/p274/p274_424.wav|32|Not that Scotland can claim the moral high ground.)
+DUMMY2/p303/p303_169.wav|44|For athletes in our current climate, their sport is their livelihood.
+DUMMY2/p252/p252_237.wav|55|You know the type.
+DUMMY2/p323/p323_115.wav|34|Parts of the system are already overstretched.
+DUMMY2/p361/p361_013.wav|79|Some have accepted it as a miracle without physical explanation.
+DUMMY2/p333/p333_356.wav|64|Which he can do.
+DUMMY2/p241/p241_029.wav|86|However, the following year the cancer returned.
+DUMMY2/p248/p248_371.wav|99|Whether his stance is shared by the incoming manager is another matter.
+DUMMY2/p260/p260_007.wav|81|The rainbow is a division of white light into many beautiful colors.
+DUMMY2/p287/p287_257.wav|77|The concerns are the same.
+DUMMY2/p263/p263_125.wav|39|It isn't a happy memory.
+DUMMY2/p277/p277_258.wav|89|Immediate action must be taken.
+DUMMY2/p363/p363_219.wav|6|It was important in training terms.
+DUMMY2/p269/p269_191.wav|94|My main concern is that public health is not put at risk.
+DUMMY2/p262/p262_020.wav|45|Many complicated ideas about the rainbow have been formed.
+DUMMY2/p273/p273_023.wav|56|If the red of the second bow falls upon the green of the first, the result is to give a bow with an abnormally wide yellow band, since red and green light when mixed form yellow.
+DUMMY2/p278/p278_029.wav|10|They have now been banned from Celtic Park for life.
+DUMMY2/p310/p310_065.wav|17|I have had no social life at all.
+DUMMY2/p255/p255_352.wav|31|He's very explosive.
+DUMMY2/p376/p376_019.wav|71|"Since then physicists have found that it is not reflection, but refraction by the raindrops which causes the rainbows. "
+DUMMY2/p263/p263_307.wav|39|Is there a waiting list ?
+DUMMY2/p249/p249_258.wav|80|They must play for each other.
+DUMMY2/p258/p258_111.wav|26|Maybe this battle has been.
+DUMMY2/p316/p316_129.wav|85|There can be no compromise on that demand.

filelists/vctk_audio_sid_text_test_filelist.txt.cleaned

+DUMMY2/p229/p229_128.wav|67|ðə hˈoʊl pɹˈɑːsɛs ɪz ɐ vˈɪʃəs sˈɜːkəl æt ðə mˈoʊmənt.
+DUMMY2/p234/p234_112.wav|3|ðæt wʊd biː ɐ sˈiəɹɪəs pɹˈɑːbləm.
+DUMMY2/p298/p298_125.wav|68|ˈaɪ ˈæskt wˌaɪ hiː hɐd kˈʌm.
+DUMMY2/p283/p283_318.wav|95|ɪf nˈɑːt, hiː ʃˌʊd ɡˌoʊ hˈoʊm.
+DUMMY2/p260/p260_046.wav|81|ɪt ɪz mˈɑːɹvələs.
+DUMMY2/p281/p281_306.wav|36|ðiːz fˈɪɡjɚz ɑːɹ tɹˈuːli ˈɔːfəl.
+DUMMY2/p285/p285_247.wav|2|nˈaʊ, sˈʌdənli, wiː hæv ðɪs nˈuː lˈændskeɪp.
+DUMMY2/p237/p237_180.wav|61|ɐ hˈɛlplaɪn nˈʌmbɚɹ ɪz pˈʌblɪʃt æt ðɪ ˈɛnd ʌv ðɪs ˈɑːɹɾɪkəl.
+DUMMY2/p259/p259_052.wav|7|mˈeɪbiː fˈʊltˈaɪm ɹˌɛfɚɹˈiːz wɪl pɹəvˈaɪd ðɪ ˈænsɚ.
+DUMMY2/p314/p314_053.wav|51|ɹˈeɪndʒɚz dɪzˈɜːvd tə bˈiːt ˌʌs.
+DUMMY2/p345/p345_070.wav|82|ˈaɪ hˈævənt mˌeɪd ˌɛni dˈɛfɪnət dᵻsˈɪʒənz.
+DUMMY2/p269/p269_132.wav|94|hˌuː wɪl ɐtˈɛnd?
+DUMMY2/p347/p347_295.wav|46|ɪt ɪz tˈɪpɪkəl ʌv mˌiː.
+DUMMY2/p251/p251_223.wav|9|fɚðə ɹˈɛfjuːdʒˌiːz, ðə ɹɪtˈɜːn wɪl nˌɑːt kˈʌm ɐ mˈoʊmənt tˈuː sˈuːn.
+DUMMY2/p300/p300_224.wav|102|ðɛɹ ɪz nˈʌθɪŋ lˈaɪk ðɪs bˈæk hˈoʊm.
+DUMMY2/p276/p276_076.wav|106|hiː kənfˈɜːmd ðætðə dˈɑːkjuːmənt wʌz vˈælɪd.
+DUMMY2/p294/p294_271.wav|104|ˈaɪ ˈɑːlsoʊ θˈɔːt, ðɪs ɪz ɐ fˈiːtʃɚ fˈɪlm.
+DUMMY2/p259/p259_257.wav|7|ðɪ ɐmˈaʊnt ʌv ˈælkəhˌɑːl æz ɐ hˈoʊl wʌz vˈɛɹi hˈaɪ.
+DUMMY2/p248/p248_131.wav|99|ðə hˈoʊl θˈɪŋ ʌv dˌuːɪŋ ðə mˈuːvi wʌzɐ ɹˈɪsk.
+DUMMY2/p334/p334_023.wav|38|ɪf ðə ɹˈɛd ʌvðə sˈɛkənd bˈoʊ fˈɔːlz əpˌɑːn ðə ɡɹˈiːn ʌvðə fˈɜːst, ðə ɹɪzˈʌlt ɪz tə ɡˈɪv ɐ bˈoʊ wɪð ɐn ɐbnˈoːɹməli wˈaɪd jˈɛloʊ bˈænd, sˈɪns ɹˈɛd ænd ɡɹˈiːn lˈaɪt wɛn mˈɪkst fˈɔːɹm jˈɛloʊ.
+DUMMY2/p345/p345_386.wav|82|ɪt ɪz kwˈaɪt sˈɪmpəl.
+DUMMY2/p330/p330_382.wav|1|nˈiːðɚ wʌz ɪnvˈɑːlvd ɪn vˈaɪələns.
+DUMMY2/p246/p246_133.wav|5|maɪ dˈɔːɾɚɹ ɪz ɐn ɐdˈʌlt.
+DUMMY2/p257/p257_140.wav|105|ɪts nˌɑːt tɹˈuː.
+DUMMY2/p340/p340_011.wav|74|wˌɛn ɐ mˈæn lˈʊks fɔːɹ sˈʌmθɪŋ bɪjˌɑːnd hɪz ɹˈiːtʃ, hɪz fɹˈɛndz sˈeɪ hiː ɪz lˈʊkɪŋ fɚðə pˈɑːt ʌv ɡˈoʊld æt ðɪ ˈɛnd ʌvðə ɹˈeɪnboʊ.
+DUMMY2/p284/p284_409.wav|16|ðˈɛn , hiː lˈæfz.
+DUMMY2/p317/p317_129.wav|97|juː wʊd biː ɹˈɔŋ.
+DUMMY2/p279/p279_183.wav|25|ɡˈʌvɚnmənt wɪl ˌɪntɚvˈiːn.
+DUMMY2/p376/p376_273.wav|71|"ɪf nˈɑːt, hiː ʃˌʊd ɡˌoʊ hˈoʊm."
+DUMMY2/p233/p233_109.wav|84|ɪt ɪz nˌɑːt ɐfˈɛktᵻd baɪ ðə sˈeɪl.
+DUMMY2/p234/p234_118.wav|3|wˌɛn wiː lˈʊkt æt ðə kˈʌmpəni.
+DUMMY2/p336/p336_207.wav|98|ðə tɹˈeɪn wʌz ˌɑːn tˈaɪm.
+DUMMY2/p227/p227_213.wav|29|wˌʌt ɑːɹ juː nˌɑːt ɡˈʊd æt ?
+DUMMY2/p347/p347_113.wav|46|ðeɪ ɑːɹ ˈɔːl ˈæɹəbz.
+DUMMY2/p317/p317_125.wav|97|ˈælən mˈɪlbɜːn, ðə hˈɛlθ sˈɛkɹətɹi, ɹɪfjˈuːzd tə kˈɑːmɛnt.
+DUMMY2/p341/p341_031.wav|66|ˈaɪ wʌz lˈɛfthˈændᵻd, bˌʌt ɪt wʌz dʒˈʌst ɐ mˈæɾɚɹ ʌv pɹˈæktɪs.
+DUMMY2/p244/p244_338.wav|78|ðɪs ˌɪzənt ɐ bɪtɹˈeɪəl ʌv pˈʌblɪk sˈɜːvɪsᵻz, ɪts ðɛɹ ɹɪnˈuːəl.
+DUMMY2/p250/p250_288.wav|24|ɪz ɪt ɪnðə ɹˈaɪt plˈeɪs ?
+DUMMY2/p233/p233_156.wav|84|ɪt ˈoʊpənz ðə dˈoːɹ tə ðə tʃˈæmpiənz lˈiːɡ.
+DUMMY2/p334/p334_118.wav|38|ðə sˈænkʃənz ɑːɹ ɐbˌaʊt kəlˈɛktɪv pˈʌnɪʃmənt.
+DUMMY2/p258/p258_027.wav|26|pˈiːpəl kˈʌm ˌɪntʊ ðə bˈoːɹdɚz fɚðə bjˈuːɾi ʌvðə bˈækɡɹaʊnd.
+DUMMY2/p341/p341_187.wav|66|hɪz sˈɪɡnɪtʃɚɹ ɪz hɪz hˈændɹaɪɾɪŋ.
+DUMMY2/p258/p258_347.wav|26|ðə kəmpˈoʊzɚ wɪl kəndˈʌkt.
+DUMMY2/p262/p262_005.wav|45|ʃiː kæn skˈuːp ðiːz θˈɪŋz ˌɪntʊ θɹˈiː ɹˈɛd bˈæɡz, ænd wiː wɪl ɡˌoʊ mˈiːt hɜː wˈɛnzdeɪ æt ðə tɹˈeɪn stˈeɪʃən.
+DUMMY2/p231/p231_174.wav|50|wˈʌn sˈiːzən, ðeɪ mˌaɪt dˈuː wˈɛl.
+DUMMY2/p363/p363_285.wav|6|bˌʌt hiː wʌz fˈɑːɹ fɹʌm ɐlˈoʊn.
+DUMMY2/p303/p303_113.wav|44|wˈɪnɪŋ, mˈiːnwaɪl, ɪz hˈɛdᵻd bˈæk tə nˈuː jˈɔːɹk sˈɪɾi.
+DUMMY2/p274/p274_181.wav|32|ɪz ɪt ɪnðə ɹˈaɪt plˈeɪs ?
+DUMMY2/p297/p297_023.wav|42|ɪf ðə ɹˈɛd ʌvðə sˈɛkənd bˈoʊ fˈɔːlz əpˌɑːn ðə ɡɹˈiːn ʌvðə fˈɜːst, ðə ɹɪzˈʌlt ɪz tə ɡˈɪv ɐ bˈoʊ wɪð ɐn ɐbnˈoːɹməli wˈaɪd jˈɛloʊ bˈænd, sˈɪns ɹˈɛd ænd ɡɹˈiːn lˈaɪt wɛn mˈɪkst fˈɔːɹm jˈɛloʊ.
+DUMMY2/p247/p247_065.wav|14|wiː wɪl pˈeɪ ðɛɹ bˈɪlz.
+DUMMY2/p273/p273_105.wav|56|ðə pɹˈɛʃɚɹ ɪz ˈɑːn ðˌɛm.
+DUMMY2/p245/p245_167.wav|59|ɪt wʌz ɐn ˈɑːd ɐfˈɛɹ, ɪn mˈɛni ɹɪspˈɛkts.
+DUMMY2/p364/p364_239.wav|88|ɪt wʌzɐ lˈɑːŋ tˈaɪm kˈʌmɪŋ.
+DUMMY2/p263/p263_047.wav|39|ðə jˈuːɡəslˌæv pɹˈɛzɪdənt sˈɛd hiː dɪdnˌɑːt ɹˈɛkəɡnˌaɪz ðɪ ɪlˈɛkʃən ˈaʊtkʌm.
+DUMMY2/p283/p283_333.wav|95|nˈoʊ fˈaɪnəl dᵻsˈɪʒən hɐzbɪn tˈeɪkən.
+DUMMY2/p335/p335_313.wav|49|ðɪ ˈɪʃuːz ɑːɹ vˈɛɹi ɪntˈɛns.
+DUMMY2/p280/p280_172.wav|52|hiː sˈɛd sˌʌm θˈɪŋz wˌɪtʃ wɜː bˈɛɾɚ lˈɛft ɐlˈoʊn.
+DUMMY2/p266/p266_006.wav|20|wˌɛn ðə sˈʌnlaɪt stɹˈaɪks ɹˈeɪndɹɑːps ɪnðɪ ˈɛɹ, ðeɪ ˈækt æz ɐ pɹˈɪzəm ænd fˈɔːɹm ɐ ɹˈeɪnboʊ.
+DUMMY2/p260/p260_027.wav|81|ɪz ðɪs ˈækjʊɹət?
+DUMMY2/p326/p326_214.wav|28|ɪts nˌɑːt lˈɑːŋ ɪnˈʌf.
+DUMMY2/p259/p259_253.wav|7|juː ɑːɹ lˈaɪk ɐn ˈænɪməl.
+DUMMY2/p228/p228_109.wav|57|haʊˈɛvɚ, ðɪ ɪntˈɛnsɪv kˈɛɹ jˈuːnɪt æt ðə sˈʌðɚn dʒˈɛnɚɹəl hˈɑːspɪɾəl wʌz fˈʊl.
+DUMMY2/p376/p376_228.wav|71|"hˈæf ʌv jˈʌŋ pˈiːpəl hɐd hɐd kˈɑːntækt wɪððə pəlˈiːs."
+DUMMY2/p361/p361_057.wav|79|ðæt wʌz sˈʌmθɪŋ ˈɛls.
+DUMMY2/p341/p341_058.wav|66|lˈeɪbɚɹ ɐkjˈuːzd ðə tˈoːɹi lˈiːdɚɹ ʌv pˈænɪkɪŋ.
+DUMMY2/p363/p363_247.wav|6|wiː ɑːɹ tˈeɪkɪŋ nˈoʊ tʃˈænsᵻz ðɪs tˈaɪm.
+DUMMY2/p262/p262_054.wav|45|ɔːlɹˈɛdi, hiː hɐzbɪn ɐ tɹəmˈɛndəs ˈɪnfluːəns ɪnðə dɹˈɛsɪŋ ɹˈuːm.
+DUMMY2/p238/p238_090.wav|37|hiː θˈɔːt ʃiː wʌz ɐmˈeɪzɪŋ.
+DUMMY2/p306/p306_020.wav|12|mˈɛni kˈɑːmplᵻkˌeɪɾᵻd aɪdˈiəz ɐbˌaʊt ðə ɹˈeɪnboʊ hɐvbɪn fˈɔːɹmd.
+DUMMY2/p238/p238_339.wav|37|hˈæɹi pˈɑːɾɚ hɐz lˈɔst hɪz mˈædʒɪk.
+DUMMY2/p302/p302_285.wav|30|ˈʌðɚz sˈɛd ðeɪ hɐdbɪn bˈiːʔn̩ baɪ pəlˈiːs.
+DUMMY2/p275/p275_377.wav|40|fˈæmɪli liːˈeɪzɑːn ˈɑːfɪsɚz ɑːɹ nˈaʊ wˈɜːkɪŋ tə səpˈoːɹt ðə fˈæmɪli.
+DUMMY2/p267/p267_286.wav|0|ænd ðeɪ wɜː bˌiːɪŋ pˈeɪd ?
+DUMMY2/p243/p243_090.wav|53|ɐmˌʌŋ ðˌɛm wʌz ɡˈæɹi ɹˈɑːbɚtsən fɹʌm dˈʌndiː.
+DUMMY2/p274/p274_213.wav|32|ɪts ˈiːzi təbi nˈɛɡətˌɪv ɐbˌaʊt ðiːz θˈɪŋz.
+DUMMY2/p286/p286_310.wav|63|bˌʌt ɪt hɐzbɪn ɐn ɐmˈeɪzɪŋ ɛkspˈiəɹɪəns.
+DUMMY2/p294/p294_293.wav|104|ðæt kˈeɪs hɐz stˈɪl nˌɑːt bˌɪn sˈɛɾəld.
+DUMMY2/p273/p273_174.wav|56|tˈuː jˈɪɹz lˈeɪɾɚ, ʃiː wʌz dˈɛd.
+DUMMY2/p231/p231_408.wav|50|ˈaɪ ʃˌʊd θˈɪŋk sˈoʊ, tˈuː.
+DUMMY2/p323/p323_084.wav|34|ˈænd, wɪðˌɪn ɪtsˈɛlf, ɪt ɪz vˈɪʒənˌɛɹi.
+DUMMY2/p248/p248_025.wav|99|ʃiː ɪz ɡˈɪvən ɐ nˈuː dˈɛpjuːɾi mˈɪnɪstɚ fɔːɹ tɹˈænspoːɹt ænd plˈænɪŋ.
+DUMMY2/p288/p288_197.wav|47|ðeɪ ɑːɹ ɪnðə jˈʊɹɹoʊ.
+DUMMY2/p300/p300_029.wav|102|ʌv kˈoːɹs, ðɪs ɪz nˈaɪs tə hˈɪɹ.
+DUMMY2/p299/p299_344.wav|58|hiː wɪl nˈɛvɚ wˈɔːk ðə stɹˈiːts ɐɡˈɛn.
+DUMMY2/p376/p376_168.wav|71|"ðeɪ wɪl dˈuː ðɛɹ ˈoʊn θˈɪŋ."
+DUMMY2/p275/p275_277.wav|40|hiː lˈʊkt vˈɛɹi ʃˈɑːɹp.
+DUMMY2/p312/p312_022.wav|62|ðɪ ˈæktʃuːəl pɹˈaɪmɚɹi ɹˈeɪnboʊ ɑːbzˈɜːvd ɪz sˈɛd təbi ðɪ ɪfˈɛkt ʌv sˈuːpɚɹɪmpəzˈɪʃən əvə nˈʌmbɚɹ ʌv bˈoʊz.
+DUMMY2/p278/p278_093.wav|10|ɪt wʌz sˌʌm tˈaɪm bɪfˌoːɹ ʃiː fˈaʊnd ˈaʊt hiː wʌz sˈeɪf.
+DUMMY2/p302/p302_312.wav|30|haʊˈɛvɚ, ðɛɹwˌʌz nˈoʊ hˈoʊp, ænd ɡlˈoːɹi tˈuː, fɔːɹ skˈɑːtlənd.
+DUMMY2/p236/p236_368.wav|75|ɪt wʌz lˈaɪk ɐ wˈiːkli wˈeɪdʒ.
+DUMMY2/p237/p237_056.wav|61|nˈoʊwˈʌn hɐz ɐpˈɪɹd ɪn kˈoːɹt ɪn ɹɪlˈeɪʃən tə hɜː dˈɛθ.
+DUMMY2/p305/p305_162.wav|54|fɔːɹ stˈɑːɹɾɚz, mˈɛnɪəv ðə skˈɑːtlənd tˈiːm dˈɪdnt tˈɜːn ˈʌp.
+DUMMY2/p275/p275_018.wav|40|ˈæɹɪstˌɑːɾəl θˈɔːt ðætðə ɹˈeɪnboʊ wʌz kˈɔːzd baɪ ɹɪflˈɛkʃən ʌvðə sˈʌnz ɹˈeɪz baɪ ðə ɹˈeɪn.
+DUMMY2/p310/p310_039.wav|17|bˌʌt wˈʌn ʃˌʊdənt ɡˌoʊ baɪ ðˈæt.
+DUMMY2/p299/p299_310.wav|58|fˈɑːɹmɚz hɐvbɪn ɐn ɛndˈeɪndʒɚd spˈiːsiːz.
+DUMMY2/p259/p259_428.wav|7|ɪn dʒˈɛnɚɹəl tˈɜːmz, ðə pɹəpˈoʊzəlz ɑːɹ vˈɛɹi mˈʌtʃ ɪn lˈaɪn wɪð ɛkspɪktˈeɪʃənz.
+DUMMY2/p339/p339_155.wav|18|ɪt ɪz dʒˈʌst ɐ mˈæɾɚɹ ʌv tˈaɪm.
+DUMMY2/p229/p229_347.wav|67|aɪv ɡɑːt nˈoʊ sˈiːkɹət.
+DUMMY2/p256/p256_308.wav|90|lˈɛts hˈoʊp ɪts ɐn ɪnvˈɛstmənt ɪnðə fjˈuːtʃɚ.
+DUMMY2/p360/p360_204.wav|60|ɪt ɪz dˈeɪndʒɚɹəs ænd ɪt ɪz ɐ lˈaɪ.
+DUMMY2/p238/p238_208.wav|37|ðə ɹˈiːfʌnd ɪz fˈʊli dʒˈʌstɪfˌaɪd.
+DUMMY2/p341/p341_319.wav|66|ðɪs ɪz vˈɛɹi bˈæd nˈuːz.
+DUMMY2/p336/p336_399.wav|98|ðə pɹˈɛʃɚɹ ɪz ɪnˈoːɹməs.
+DUMMY2/p229/p229_067.wav|67|ðæt wʌzðɪ ˈiːzi ɪlˈɛkʃən.
+DUMMY2/p329/p329_159.wav|103|nˈoʊwˈʌn, nˌɑːt ˈiːvən ðə skˈɑːɾɪʃ ˈɑːɹts kˈaʊnsəl, wʌz ˈɪntɹəstᵻd ɪn hɜː.
+DUMMY2/p258/p258_304.wav|26|ðə kˈɑːnfɪdəns ɪz lˈoʊ, bˌʌt ɪt ɪz ɐ dˈɪfɪkəlt θˈɪŋ tʊ ˌʌndɚstˈænd.
+DUMMY2/p312/p312_033.wav|62|hˈævənt bˌɪn sˌoʊ lˈʌki sˈɪns.
+DUMMY2/p266/p266_093.wav|20|tˈuː ˈʌðɚ mˈɛn, ɪnklˈuːdɪŋ ðə tˈæksi dɹˈaɪvɚ, wɜː wˈuːndᵻd ɪnðɪ ɐtˈæk.
+DUMMY2/p307/p307_396.wav|22|ɪt wʌz ˈɜːli mˈɔːɹnɪŋ.
+DUMMY2/p326/p326_039.wav|28|ðɛɹ ɪz nˈʌθɪŋ lˈaɪk ðɪs bˈæk hˈoʊm.
+DUMMY2/p333/p333_009.wav|64|ðɛɹˈɪz , ɐkˈoːɹdɪŋ tə lˈɛdʒənd, ɐ bˈɔɪlɪŋ pˈɑːt ʌv ɡˈoʊld æt wˈʌn ˈɛnd.
+DUMMY2/p295/p295_154.wav|92|ˈaɪ ɹɪmˈɛmbɚɹ ɪt klˈɪɹli.
+DUMMY2/p297/p297_007.wav|42|ðə ɹˈeɪnboʊ ɪz ɐ dɪvˈɪʒən ʌv wˈaɪt lˈaɪt ˌɪntʊ mˈɛni bjˈuːɾɪfəl kˈʌlɚz.
+DUMMY2/p233/p233_153.wav|84|ɪt wʊd biː ɐ lˈæst ɹɪzˈɔːɹt.
+DUMMY2/p244/p244_220.wav|78|ðɪs jˈɪɹ, ɪt wɪl ɐmˈaʊnt tʊ ɐ fjˈuː hˈʌndɹəd θˈaʊzənd pˈaʊndz.
+DUMMY2/p267/p267_136.wav|0|ɪt hɐz bɪkˌʌm ɐ wˈeɪ ʌv lˈaɪf.
+DUMMY2/p311/p311_313.wav|4|ðə dᵻsˈɪʒən wʌz lˈɛft ɛntˈaɪɚli tə hˌɪm.
+DUMMY2/p230/p230_113.wav|35|juː kæn spˈɛnd mˈʌni ˌɑːn hˈaʊzɪŋ.
+DUMMY2/p318/p318_295.wav|19|wiː ɡˈeɪv ðˌɛm ðə ɡˈoʊl.
+DUMMY2/p236/p236_090.wav|75|ˈæftɚ ðə mˈætʃ, dˈuː juː ?
+DUMMY2/p364/p364_156.wav|88|fˈɜːɡəsən hɐd dˈʌn hɪz hˈoʊmwɜːk.
+DUMMY2/p310/p310_260.wav|17|ðæt ɪz maɪ ɹˈoʊl.
+DUMMY2/p323/p323_261.wav|34|ðeɪ hˈoʊpt tə ɹɪmˈeɪn ɪnðɪ ˈɛdɪnbʌɹə ˈɛɹiə.
+DUMMY2/p284/p284_393.wav|16|ɑːnðə kˈɑːntɹɛɹi, ɪt wʌz ˈæktʃuːəli vˈɛɹi fˈʌni.
+DUMMY2/p276/p276_460.wav|106|wiː wɪl pˈeɪ ðɛɹ bˈɪlz.
+DUMMY2/p363/p363_273.wav|6|ðə plˈɑːt ɪz mˈɪnɪməl.
+DUMMY2/p250/p250_039.wav|24|kˈɔsts hæv ɡɑːt təbi kəntɹˈoʊld.
+DUMMY2/p317/p317_244.wav|97|ðɪs ɪvˈɛnt ɐlˈaʊz ˌʌs tʊ ˈɛmfɐsˌaɪz ðə pˈɑːzɪtˌɪv.
+DUMMY2/p280/p280_042.wav|52|hiː dʌznˌɑːt ˈiːvən tɹˈʌst hɪz ˈoʊn mˈɛmbɚz.
+DUMMY2/p227/p227_342.wav|29|hæv ɐ lˈʊk æt ðɪs lˈɑːt.
+DUMMY2/p333/p333_255.wav|64|bˌʌt ðə fˈɔːɹən sˈɛkɹətɹi kæn kˈoʊp.
+DUMMY2/p232/p232_103.wav|96|wiː ɹˈɛkəɡnˌaɪz ðɪ ɪmpˈoːɹtənt ɹˈoʊl ʌv ɡˈɑːlf ɪn ɐtɹˈæktɪŋ vˈɪzɪɾɚz.
+DUMMY2/p305/p305_138.wav|54|ɐnˈʌðɚ sədʒˈɛstᵻd ðə kˈʌmpəni ʃˌʊd kˈæɹi ˈoʊnli pədˈɛstɹiənz.
+DUMMY2/p248/p248_196.wav|99|ɪt ɪz nˌɑːt sˈæɾɪsfˌaɪd wɪððə stˈændɚd ʌv fˈaɪɚ sˈeɪfti pɹəvˈɪʒənz.
+DUMMY2/p230/p230_166.wav|35|wiː bɪlˈiːv ɪnðə mˈiːdiəm tˈɜːm.
+DUMMY2/p303/p303_275.wav|44|ðɛɹˌɑːɹ lˈɑːts ʌv ðiːz wˈɪmɪn ɪn fˈɪnlənd.
+DUMMY2/p280/p280_208.wav|52|ɡˈæs pɹədˈʌkʃən wʌz ˈɑːlsoʊ æt ɹˈɛkɚd lˈɛvəlz lˈæst jˈɪɹ.
+DUMMY2/p330/p330_252.wav|1|ˈaɪ fˈɜːst mˈɛt hˌɪm lˈæst sˈʌmɚ.
+DUMMY2/p330/p330_209.wav|1|ˈaɪ wɪl nˌɑːt tˈeɪk juː ˌaʊɾəv kˈɑːntɛkst.
+DUMMY2/p240/p240_214.wav|93|ɪt hɐd ˈɔːl bˌɪn ɐɹˈeɪndʒd.
+DUMMY2/p293/p293_185.wav|23|ðɪs ɪz ðə stˈʌf ʌv lˈaɪv mjˈuːzɪk.
+DUMMY2/p237/p237_230.wav|61|klˈɪɹli, ðə stˈeɪks ɑːɹ hˈaɪ.
+DUMMY2/p277/p277_014.wav|89|tə ðə hˈiːbɹuːz ɪt wʌzɐ tˈoʊkən ðæt ðɛɹ wʊd biː nˈoʊmˌoːɹ jˌuːnɪvˈɜːsəl flˈʌdz.
+DUMMY2/p251/p251_107.wav|9|ɪt hɐdbɪn plˈeɪd æt fˈɛstɪvəlz.
+DUMMY2/p302/p302_011.wav|30|wˌɛn ɐ mˈæn lˈʊks fɔːɹ sˈʌmθɪŋ bɪjˌɑːnd hɪz ɹˈiːtʃ, hɪz fɹˈɛndz sˈeɪ hiːz lˈʊkɪŋ fɚðə pˈɑːt ʌv ɡˈoʊld æt ðɪ ˈɛnd ʌvðə ɹˈeɪnboʊ.
+DUMMY2/p264/p264_147.wav|65|ʃiːz bˌɪn ʃˈɑːt.
+DUMMY2/p236/p236_288.wav|75|bɹˈaʊn ɪz ɐn ˈɪntɹəstɪŋ mˈæn, bˌʌt hiː ɪz nˌɑːt dˈɛspɚɹət.
+DUMMY2/p323/p323_297.wav|34|aɪv ɡɑːt ðə ʃˈɜːt.
+DUMMY2/p297/p297_402.wav|42|ˈaɪ dˈoʊnt hæv ɐ pɹˈɑːbləm wɪð ɡˌɛɾɪŋ ˈoʊldɚ.
+DUMMY2/p267/p267_182.wav|0|ɐ tˈiːm ɪz ɐ tˈiːm.
+DUMMY2/p226/p226_121.wav|43|mˈeɪbiː ðɪs bˈæɾəl hɐzbɪn.
+DUMMY2/p311/p311_226.wav|4|ɡɔn wɪð ðˌɛm ɪz ˌɛni sˈɛns ʌv nˈæɹətˌɪv.
+DUMMY2/p335/p335_279.wav|49|ɔːɹ ɹˈæðɚ hiː dˈɪd ænd hiː dˈɪdnt.
+DUMMY2/p270/p270_068.wav|8|ðˈɛn fˈɑːloʊd ɐ bˈaʊt ʌv flˈuː.
+DUMMY2/p260/p260_072.wav|81|ɪt wʌz mˈædʒɪk.
+DUMMY2/p362/p362_341.wav|15|ðə ɹɪzˈʌlt kʊd biː ˈɔːl dˌaʊn tə tˈɜːnaʊt.
+DUMMY2/p228/p228_180.wav|57|wˈʌn sˈiːzən, ðeɪ mˌaɪt dˈuː wˈɛl.
+DUMMY2/p316/p316_152.wav|85|fˈeɪlɪɹ ɪz nˌɑːt ɐn ˈɑːpʃən.
+DUMMY2/p317/p317_423.wav|97|mˈæntʃɛstɚ juːnˈaɪɾᵻd ɑːɹ ðə klˈæsɪk ɛɡzˈæmpəl.
+DUMMY2/p243/p243_292.wav|53|ɪts wˈɜːk ɪnklˈuːdz dˈiːlɪŋ wɪð tʃˈaɪld ɐbjˈuːs.
+DUMMY2/p362/p362_054.wav|15|wiː sˈɜːtənli hˈoʊp wiː hɐvbɪn səksˈɛsfəl.
+DUMMY2/p243/p243_305.wav|53|wˌʌt hˈæpənd ɪn ðæt ɡˈeɪm ?
+DUMMY2/p364/p364_297.wav|88|ɪt wʌz dʒˈʌst wˈʌn mˈæn.
+DUMMY2/p255/p255_049.wav|31|wiː wɜː sɚpɹˈaɪzd tə sˈiː ðə fˈoʊɾəɡɹˌæf.
+DUMMY2/p297/p297_358.wav|42|hiː sˈɛd hiː hɐd nˈoʊ ɹɪpˈoːɹts ʌv kˈæʒuːəlɾɪz.
+DUMMY2/p283/p283_430.wav|95|maɪ ˈeɪm ɪz ɐ tˈɑːp sˈɪks fˈɪnɪʃ.
+DUMMY2/p310/p310_300.wav|17|mˈaɪk tˈaɪsən wɛnt tə pɹˈɪzən.
+DUMMY2/p363/p363_051.wav|6|ðə nˈeɪʃən hɐz hɪz mjˈuːzɪk.
+DUMMY2/p261/p261_112.wav|100|ɪt bɪkˌeɪm ɐ nˈæʃənəl nˈɛtwɜːk.
+DUMMY2/p234/p234_036.wav|3|ɪt wʌz sˈoʊld æɾə lˈɔs.
+DUMMY2/p247/p247_470.wav|14|ðeɪ wɜː ɡˈʊd jˈɪɹz fɔːɹ hˌɪm.
+DUMMY2/p303/p303_269.wav|44|ˈæftɚ ðæt nˈʌθɪŋ kʊd sˈeɪv hˌɪm.
+DUMMY2/p317/p317_256.wav|97|ðə mˈæn wʌz pɹənˈaʊnst dˈɛd ˌɑːn ɐɹˈaɪvəl.
+DUMMY2/p351/p351_161.wav|33|pˈæɾɚsən kæn ɐfˈoːɹd təbi dʒˈɛnɚɹəs.
+DUMMY2/p314/p314_295.wav|51|juː tˈeɪk ɐ ɹˈɪsk.
+DUMMY2/p293/p293_268.wav|23|ˌaʊɚ tʃˈɪldɹən ɑːɹ ˌaʊɚ fjˈuːtʃɚ.
+DUMMY2/p306/p306_352.wav|12|hˌuː hɐz ðə sˈɛkənd hˈaɪəst?
+DUMMY2/p273/p273_098.wav|56|ðə fˈɑːloʊɪŋ ɑːɹ ðə pɹˈɪnsɪpəl pɹəvˈɪʒənz.
+DUMMY2/p285/p285_029.wav|2|ðɛɹ kˈɜːɹɪdʒ, ænd ðɛɹ ˈɑːnɪsti, ʃˌʊd biː ɹɪspˈɛktᵻd.
+DUMMY2/p266/p266_073.wav|20|ɪt wˈɜːks fɔːɹ ˌʌs.
+DUMMY2/p374/p374_288.wav|11|ˈaɪ hɐd ɐ ɡˈʊd lˈaɪf æt ɹˈeɪndʒɚz.
+DUMMY2/p280/p280_171.wav|52|juː nˈiːd ɐ lˈɑːŋtˈɜːm stɹˈæɾədʒi ɪn fˈʊtbɔːl.
+DUMMY2/p239/p239_203.wav|48|ɪt ɪz ˈɔːl tə dˈuː wɪððə kˈoʊtʃɪŋ.
+DUMMY2/p287/p287_292.wav|77|ɪn ˈɛsəns, ðə tˈiːtʃɪŋ pɹəfˈɛʃən hɐz ɐ tʃˈɔɪs.
+DUMMY2/p330/p330_112.wav|1|wˈɑːlᵻs wʌz ɪn æt ðə dˈiːp ˈɛnd.
+DUMMY2/p247/p247_141.wav|14|ðeɪ mˌeɪd sˈʌtʃ dᵻsˈɪʒənz ɪn lˈʌndən.
+DUMMY2/p277/p277_050.wav|89|ðɪs ɹˌɛpɹɪzˈɛnts ɐ tˈʌf ɡˈeɪm fɔːɹ ˌʌs.
+DUMMY2/p233/p233_289.wav|84|hiː lˈʊkt vˈɛɹi ʃˈɑːɹp.
+DUMMY2/p284/p284_103.wav|16|mˈiːnwaɪl, ðə skˈɑːɾɪʃ kənsˈuːmɚ kˈaʊnsəl jˈɛstɚdˌeɪ ˈɑːfɚd səpˈoːɹt fɚðə nˈuː bˈɪl.
+DUMMY2/p334/p334_366.wav|38|wiː wɪl mˈɪs hˌɪm vˈɛɹi mˈʌtʃ.
+DUMMY2/p238/p238_196.wav|37|tˈaɪɡɚɹ ɪz nˌɑːt ðə nˈɔːɹm.
+DUMMY2/p304/p304_193.wav|72|ðˈɛn ðeɪ wɜːɹ ɐwˈɔːɹdᵻd ɐ pˈɛnəlɾi.
+DUMMY2/p229/p229_348.wav|67|lˈʊk æt ðə wˈɪtnəsᵻz.
+DUMMY2/p268/p268_147.wav|87|hˌaʊ dˈuː juː ɡɛt ɪt bˈæk ?
+DUMMY2/p293/p293_348.wav|23|hiː kwˈɪt ɪn ɑːktˈoʊbɚ.
+DUMMY2/p341/p341_082.wav|66|dʒˈɑːn ɹˈiːd, ðə nˈɔːɹðɚn ˈaɪɚlənd sˈɛkɹətɹi, jˈɛstɚdˌeɪ ɐpˈiːld fɔːɹ ɹɪstɹˈeɪnt.
+DUMMY2/p258/p258_097.wav|26|ɪt ɪz ɐ ɡˈʊd lˈaɪfstaɪl.
+DUMMY2/p340/p340_220.wav|74|nˌɑːt sˈoʊ, ɪt sˈiːmz.
+DUMMY2/p269/p269_174.wav|94|mˈɑːɹk fˈɪʃɚ wʌzɐ ɡˈɛst ʌvðə nˈɔːɹðɚn ˈaɪɚlənd tˈʊɹɪst bˈoːɹd.
+DUMMY2/p270/p270_078.wav|8|aɪvhˌæd ɪt fɚðɪ ɛɡzˈæmz.
+DUMMY2/p334/p334_224.wav|38|ˈaɪ kˈænt blˈeɪm ðə fˈænz.
+DUMMY2/p307/p307_306.wav|22|wɪɹ tˈɔːkɪŋ ɐbˌaʊt kɹiːˈeɪɾɪŋ ɐn ɐtɹˈæktɪv nˈeɪbɚhˌʊd.
+DUMMY2/p361/p361_205.wav|79|tɹænslˈeɪʃən wiː ɡɑːt ɪt ɹˈɔŋ.
+DUMMY2/p229/p229_142.wav|67|wˌʌt wɪl hˈæpən ðˈɛn ?
+DUMMY2/p310/p310_221.wav|17|wiː wɪl lˈʊk ˌɪntʊ ɪt.
+DUMMY2/p232/p232_357.wav|96|hiː hɐd plˈeɪd wˈɛl ɪn ðæt sˈɛntɹəl ɹˈoʊl.
+DUMMY2/p263/p263_389.wav|39|ðɪs sˈiːzən hɐzbɪn ɐ nˈaɪtmɛɹ.
+DUMMY2/p283/p283_273.wav|95|dˈɪd hiː tɹˈɪp ?
+DUMMY2/p374/p374_277.wav|11|wˌɛɹ dˈuː juː stˈɑːɹt?
+DUMMY2/p301/p301_289.wav|91|tʃˈɪldɹən ɑːɹ jˈuːzɪŋ bˈʊks ɪn ɐ tˈɛɹəbəl kəndˈɪʃən.
+DUMMY2/p345/p345_267.wav|82|hɜː pɹˈɛzəns wʌz ˈɔːlmoʊst ˈɛvɹɪwˌɛɹ.
+DUMMY2/p264/p264_226.wav|65|nˈoʊ pˈɑːɹtnɚz wʊd lˈuːz ðɛɹ dʒˈɑːbz.
+DUMMY2/p253/p253_050.wav|70|ɐ nˈeɪbɚ sˈɛd.
+DUMMY2/p276/p276_118.wav|106|ɪf ðeɪ lˈaɪkt ɪt ðˈɛn aɪl biː hˈæpi.
+DUMMY2/p295/p295_175.wav|92|ˈɛnɪθˌɪŋ ðæt kæn biː dˈʌn, ðə ɡˈʌvɚnmənt wɪl dˈuː.
+DUMMY2/p247/p247_466.wav|14|ˈaɪ θˈɪŋk ɪts ɐ ɡɹˈeɪt sˈɪstəm.
+DUMMY2/p301/p301_182.wav|91|ˈaɪ sˈiː sˈoʊʃəl wˈɜːk æz ɐ voʊkˈeɪʃən, ɐ kəmˈɪtmənt.
+DUMMY2/p294/p294_156.wav|104|wiː ɑːɹ wˈɛl ɪnʃˈʊɹd.
+DUMMY2/p287/p287_190.wav|77|wiː hæv tə ɹˈɛkəɡnˌaɪz ðæt hiː ɪz ɐn ɪlˈuːsɪv kˈæɹɪktɚ.
+DUMMY2/p258/p258_333.wav|26|ɹˈɑːbɚt ɪz ɐ spˈɛʃəl tˈælənt.
+DUMMY2/p275/p275_122.wav|40|hˌuː wˈʊdhæv?
+DUMMY2/p231/p231_259.wav|50|ɪt wʌzðə klˈaɪmæks ʌvðə θˈɪŋ.
+DUMMY2/p330/p330_073.wav|1|ˌoʊvɚ tˈaɪm, wɪð pˈeɪʃəns ænd pɹɪsˈɪʒən, ðə tˈɛɹɚɹˌɪsts wɪl biː pɚsˈuːd.
+DUMMY2/p277/p277_239.wav|89|ˈaɪ ʃˌʊd θˈɪŋk sˈoʊ, tˈuː.
+DUMMY2/p374/p374_352.wav|11|æz ɪf ðeɪ ˈɛvɚ stˈɑːpt.
+DUMMY2/p244/p244_258.wav|78|ɪf ɪt dˈʌzənt, ɪt dˈʌzənt.
+DUMMY2/p277/p277_194.wav|89|ˈaɪ wʊd θˈɪŋk ɐbˌaʊt ðɪ ˈɛnd ʌv dʒˈænjuːˌɛɹi, ðə bɪɡˈɪnɪŋ ʌv fˈɛbɹuːˌɛɹi.
+DUMMY2/p241/p241_177.wav|86|ðə klˈæɹɪɾi ɪz vˈaɪɾəl.
+DUMMY2/p247/p247_275.wav|14|wˌʌt fˈɔːɹm dˈɪd ðæt tˈeɪk ?
+DUMMY2/p230/p230_230.wav|35|ðɐthɐzbˌɪn ðɪ ˈiːzi pˈɑːɹt.
+DUMMY2/p323/p323_015.wav|34|ðə ɡɹˈiːks jˈuːzd tʊ ɪmˈædʒɪn ðˌɐɾɪt wʌzɐ sˈaɪn fɹʌmðə ɡˈɑːdz tə foːɹtˈɛl wˈɔːɹ ɔːɹ hˈɛvi ɹˈeɪn.
+DUMMY2/p269/p269_365.wav|94|bˌʌt ðə ɹˈiːəl pɹˈɑːbləm ɪz ðə klˈoʊʒɚɹ ʌvðɪ ˈɛkspoːɹt mˈɑːɹkɪt.
+DUMMY2/p310/p310_049.wav|17|ðeɪ hɐd fˈoːɹ tʃˈɪldɹən təɡˈɛðɚ.
+DUMMY2/p281/p281_068.wav|36|ˈaɪ hæv pɹˈuːvd ðæt ɪnðə pˈæst.
+DUMMY2/p343/p343_162.wav|21|dˈænsɪŋ wʌz hɜː lˈaɪf.
+DUMMY2/p299/p299_208.wav|58|aɪm ɐ bˈɪt ɐnˈɔɪd.
+DUMMY2/p329/p329_292.wav|103|ðə mˈɛθɐdˌoʊn pɹˈoʊɡɹæm ɪz kəmplˈiːtli ˌaʊɾəv kəntɹˈoʊl.
+DUMMY2/p232/p232_376.wav|96|hiː kʊd mˈeɪk ɪt.
+DUMMY2/p305/p305_135.wav|54|ˈaɪ kʊd hˈɑːɹdli kˈiːp ˌʌp wɪð pɹəfˈɛsɚ məkˈiːn.
+DUMMY2/p351/p351_231.wav|33|wiː ɑːɹ pɚsˈuːɪŋ lˈiːɡəl ˈækʃən ɐɡˈɛnst ðə ɡˈʌvɚnmənt.
+DUMMY2/p265/p265_153.wav|73|mˈɪlətˌɛɹi ˈækʃən ɪz ðɪ ˈoʊnli ˈɑːpʃən wiː hæv ɑːnðə tˈeɪbəl tədˈeɪ.
+DUMMY2/p323/p323_137.wav|34|ˈɛvɹɪθˌɪŋ wʌzɐ dˈɛd ˈɛnd.
+DUMMY2/p305/p305_176.wav|54|ðæt hɐz ɡˈɪvən mˌiː ɡɹˈeɪt kˈɑːnfɪdəns.
+DUMMY2/p238/p238_053.wav|37|dˈʌz ɪt mˈæɾɚ ?
+DUMMY2/p230/p230_195.wav|35|ɪt ɪz nˌɑːt ˈɔːl ɡˈʊd nˈuːz ænd ɹɪlˈiːf fɔːɹ lˈeɪbɚ, haʊˈɛvɚ.
+DUMMY2/p238/p238_093.wav|37|hiː sˈiːmz tə hæv ˈɛvɹɪθˌɪŋ.
+DUMMY2/p259/p259_323.wav|7|wiː fˈiːl vˈɛɹi kˈʌmftəbəl ɪn ðɪs ˌɪntɚnˈæʃənəl ɛnvˈaɪɹənmənt.
+DUMMY2/p285/p285_032.wav|2|ðɪs ɪz ðə wˈɪndoʊ.
+DUMMY2/p302/p302_208.wav|30|wˌɪtʃ mˈiːnz ɪt mˈæɾɚz.
+DUMMY2/p231/p231_176.wav|50|ðɪs mˈʌtʃ ˈaɪ kæn tˈɛl juː.
+DUMMY2/p301/p301_054.wav|91|hˈɪɹ hiː ɪz, ɪn ɪfˈɛkt, ɐpˈɔɪntɪŋ hɪmsˈɛlf ɐ dʒˈʌdʒ.
+DUMMY2/p310/p310_102.wav|17|wiːʃˌɐl ɹɪlˈaɪ ˌɑːn hjˈuːmən bˈiːɪŋz.
+DUMMY2/p305/p305_121.wav|54|ɪt ɪz ɐ vˈɪʃəs sˈɜːkəl.
+DUMMY2/p231/p231_458.wav|50|ʃiː hɐz ɹˈiːtʃt ðə tˈɑːp ʌv hɜː pɹəfˈɛʃən.
+DUMMY2/p311/p311_024.wav|4|ðɪs ɪz ɐ vˈɛɹi kˈɑːmən tˈaɪp ʌv bˈoʊ, wˈʌn ʃˈoʊɪŋ mˈeɪnli ɹˈɛd ænd jˈɛloʊ, wɪð lˈɪɾəl ɔːɹ nˈoʊ ɡɹˈiːn ɔːɹ blˈuː.
+DUMMY2/p245/p245_248.wav|59|ɪz ðɛɹ ˌɑːn hɪz hˈændz?
+DUMMY2/p333/p333_311.wav|64|kˈaʊnsɪlɚ ɡˈoːɹdən hɐz ɹɪfjˈuːzd tə stˈænd dˈaʊn.
+DUMMY2/p299/p299_007.wav|58|ðə ɹˈeɪnboʊ ɪz ɐ dɪvˈɪʒən ʌv wˈaɪt lˈaɪt ˌɪntʊ mˈɛni bjˈuːɾɪfəl kˈʌlɚz.
+DUMMY2/p229/p229_333.wav|67|ʃiː dɪdnˌɑːt ɐtˈɛnd ðə kˈoːɹtɹuːm.
+DUMMY2/p307/p307_286.wav|22|ðə bˈoːɹd wʊd ɹɪpˈoːɹt tə ðə skˈɑːɾɪʃ pˈɑːɹləmənt.
+DUMMY2/p305/p305_414.wav|54|ɪt ɪz ðə hˈɑːlɪdˌeɪ pɹˈoʊɡɹæm wɪð ɐ mˈɔːɹɡɪdʒ.
+DUMMY2/p264/p264_140.wav|65|hiː nˌɪɹli kˈɪld maɪ sˈʌn.
+DUMMY2/p374/p374_114.wav|11|ˈaɪ dˈoʊnt θˈɪŋk ɪt wʊd mˌeɪk ˌɛni dˈɪfɹəns.
+DUMMY2/p363/p363_369.wav|6|wiː hɐvbɪn ˌoʊvɚwˈɛlmd baɪ ðə ɹɪspˈɑːns.
+DUMMY2/p293/p293_374.wav|23|ˈaɪ dˈoʊnt θˈɪŋk ðə ɹˌɛfɚɹˈiːz ɑːɹ ɐɡˈɛnst ˌʌs.
+DUMMY2/p316/p316_329.wav|85|ɪts ɐ pɹədˈʌkʃən kˈʌmpəni.
+DUMMY2/p236/p236_018.wav|75|ˈæɹɪstˌɑːɾəl θˈɔːt ðætðə ɹˈeɪnboʊ wʌz kˈɔːzd baɪ ɹɪflˈɛkʃən ʌvðə sˈʌnz ɹˈeɪz baɪ ðə ɹˈeɪn.
+DUMMY2/p234/p234_332.wav|3|bˌʌt ɪt kæn biː dˈʌn.
+DUMMY2/p277/p277_132.wav|89|nˈoʊ pɹədˈʌkʃən wʌz ɐtʃˈiːvd.
+DUMMY2/p326/p326_205.wav|28|æz ɐɡɹˈiːd, ðə pɹˈaɪm mˈɪnɪstɚ wʌz dɹˈɪvən tə wˈɛstmɪnstɚ hˈɔːl.
+DUMMY2/p272/p272_134.wav|69|ðɪs tˈʊɹ ɪz kɹˈɪɾɪkəl fɔːɹ nˈuː zˈiːlənd ɹˈʌɡbi.
+DUMMY2/p316/p316_125.wav|85|ænd nˈaʊ ðə pɹˈɛʃɚɹ ɪz ˈɔf.
+DUMMY2/p274/p274_149.wav|32|ˈaɪ pɹɪfˈɜː ðə klˈæɹɪɾi ʌvðɪ ɛɡzˈɪstɪŋ sˈɪstəm.
+DUMMY2/p227/p227_368.wav|29|ɐ kɹˈuːʃəl mˈoʊmənt hɐz ɐɹˈaɪvd.
+DUMMY2/p334/p334_206.wav|38|wiːl hæv tə wˈɜːk hˈɑːɹd tədˈeɪ.
+DUMMY2/p339/p339_087.wav|18|ˈaɪ æm nˌɑːt kəmplˈiːtli ɪnsˈeɪn.
+DUMMY2/p286/p286_453.wav|63|hiː wʌz sˈɛd təbi ɪmˈoʊʃənəli dɪstˈɜːbd.
+DUMMY2/p301/p301_110.wav|91|pˈiːpəl wˈɑːnt tə sˈiː mˌiː ɑːnðə skɹˈiːn.
+DUMMY2/p282/p282_188.wav|83|sˈʌdənli, ðə ɹˈʌɡbi wˈɜːld hɐd tʃˈeɪndʒd.
+DUMMY2/p263/p263_147.wav|39|lˈuːzɪŋ ɪn ðæt mˈænɚɹ ɪz vˈɛɹi hˈɑːɹd tə tˈeɪk.
+DUMMY2/p256/p256_253.wav|90|ˈaɪ wʌz nˈɛvɚ ɡˌoʊɪŋ tə plˈeɪ ɐɡˈɛnst skˈɑːtlənd.
+DUMMY2/p374/p374_165.wav|11|sˈʌmθɪŋ hɐz ɡɑːt tə tʃˈeɪndʒ.
+DUMMY2/p262/p262_232.wav|45|ɪts vˈɛɹi sˈeɪf.
+DUMMY2/p267/p267_417.wav|0|ðɪs ɪz nˈoʊ ɹɪflˈɛkʃən ˌɑːn ɹˈeɪndʒɚz.
+DUMMY2/p240/p240_078.wav|93|aɪv ɡɑːt ðə ʃˈɜːt.
+DUMMY2/p347/p347_143.wav|46|ðɛɹ ɪz nˈoʊ sˈaɪn ʌv ˈɛnɪwˌʌn bˌiːɪŋ hˈɜːt.
+DUMMY2/p245/p245_069.wav|59|ʃiː dˈaɪd ɪn hˈɑːspɪɾəl tˈuː ˈaɪʊɹz lˈeɪɾɚ.
+DUMMY2/p233/p233_172.wav|84|ðeɪ sˈeɪ ðæt vˈaɪɾəl ˈɛvɪdəns wʌz nˌɑːt hˈɜːd ɪn kˈoːɹt.
+DUMMY2/p280/p280_282.wav|52|ˌoʊvɚɹˈɔːl, ðə lˈæst hˈoʊl wʌz ɡˈʊd tə ðə wˈɪmɪn.
+DUMMY2/p298/p298_364.wav|68|aɪm lˈʊkɪŋ æt wˈeɪz tə dˈuː ðæt nˈaʊ.
+DUMMY2/p339/p339_240.wav|18|ðə tˈiːtʃɚ wʊdhɐv ɐpɹˈuːvd.
+DUMMY2/p361/p361_387.wav|79|wiː hɐvbɪn ɡˌoʊɪŋ fɔːɹ θɹˈiː jˈɪɹz.
+DUMMY2/p278/p278_221.wav|10|dʒˈænjuːˌɛɹi ɪz ɐ bˈæd tˈaɪm ʌv jˈɪɹ.
+DUMMY2/p334/p334_289.wav|38|ðeɪ mˈæɹɪd ɪn ˈɔːɡəst lˈæst jˈɪɹ.
+DUMMY2/p250/p250_187.wav|24|ðɪs tʃˈæmpiənʃˌɪp ɪz dˈɪfɹənt fɹʌmðɪ ˈʌðɚ mˈeɪdʒɚz.
+DUMMY2/p248/p248_283.wav|99|mˈæloʊni ɪz ɐn ɛnɡˈeɪdʒɪŋ tˈælənt.
+DUMMY2/p275/p275_261.wav|40|ɪt wɪl biː dˈʌn ɪn stˈeɪdʒᵻz.
+DUMMY2/p288/p288_024.wav|47|ðɪs ɪz ɐ vˈɛɹi kˈɑːmən tˈaɪp ʌv bˈoʊ, wˈʌn ʃˈoʊɪŋ mˈeɪnli ɹˈɛd ænd jˈɛloʊ, wɪð lˈɪɾəl ɔːɹ nˈoʊ ɡɹˈiːn ɔːɹ blˈuː.
+DUMMY2/p271/p271_454.wav|27|ɪts ɐ mˈɪɹəkəl.
+DUMMY2/p252/p252_408.wav|55|ðeɪ hædtə hæv hˈɑːspɪɾəl tɹˈiːtmənt.
+DUMMY2/p261/p261_192.wav|100|ɪt wʌzɐ pɹˈiːˈɛmptɪv stɹˈaɪk.
+DUMMY2/p308/p308_099.wav|107|ɡlˈæzɡoʊ dɪzˈɜːvd ðɛɹ wˈɪn, bˌʌt wiː mˌeɪd ðˌɛm lˈʊk ɡˈʊd.
+DUMMY2/p288/p288_070.wav|47|nˈiːðɚɹ ɪt ˈɪz.
+DUMMY2/p317/p317_356.wav|97|wɪɹ nˌɑːt ɐn ɛmplˈɔɪmənt ˈeɪdʒənsi.
+DUMMY2/p351/p351_251.wav|33|ðæt ɪz ɐ mˈæɾɚ fɚðə skˈɑːɾɪʃ pˈɑːɹləmənt.
+DUMMY2/p329/p329_075.wav|103|ðɪs wɪl biː nˈoʊ ˈiːzi ˈɑːpʃən.
+DUMMY2/p261/p261_180.wav|100|aɪv bˌɪn ɪn tˈuː fˈaɪnəlz, ænd aɪv ɡɑːt ɐ mˈɛdəl.
+DUMMY2/p301/p301_272.wav|91|dɹˈɪŋk ænd pˈɛtɹəl pɹˈaɪsᵻz ɹɪmˈeɪn ʌntˈʌtʃt.
+DUMMY2/p277/p277_404.wav|89|wˈɛðɚ ðə hˈaɪ kˈoːɹt wɪl ˌɪntəfˈɪɹ wɪððə sˈɛntəns ɪz ɐnˈʌðɚ mˈæɾɚ.
+DUMMY2/p301/p301_135.wav|91|hˌaʊ ɡˈʊd ɪz lˈɛnɑːks lˈuːiz?
+DUMMY2/p246/p246_333.wav|5|tˈuː pˈiːpəl wɜːɹ ˈɪntɚvjˌuːd.
+DUMMY2/p340/p340_250.wav|74|ðə fˈɪlm wʌz ɡɹˈeɪt.
+DUMMY2/p268/p268_355.wav|87|ðeɪ hɐd dᵻklˈaɪnd ɪn ˈiːtʃ əv ðə tˈuː pɹɪsˈiːdɪŋ kwˈɔːɹɾɚz.
+DUMMY2/p236/p236_143.wav|75|ðə hˈoʊl ˈɪndʌstɹi ɪz ɐ ʃˈæmbəlz.
+DUMMY2/p231/p231_398.wav|50|ðeɪ hæv fˈeɪld tə dɪlˈɪvɚ.
+DUMMY2/p340/p340_322.wav|74|ˈaɪ æm ɛkstɹˈiːmli kˈɔːʃəs.
+DUMMY2/p228/p228_048.wav|57|ðə skˈɑːɾɪʃ pˈɑːɹləmənt ɪz ˈɑːlsoʊ lˈʊkɪŋ æt sˈɪmɪlɚ mˈɛʒɚz.
+DUMMY2/p334/p334_193.wav|38|ɪt ɪz ɪn ˌaʊɚɹ ˈoʊn hˈændz.
+DUMMY2/p226/p226_128.wav|43|ˈaɪ fˈɛlt vˈɛɹi stɹˈɔŋli ðæt ˈɪŋɡlənd ʃʊdhˈævɪt.
+DUMMY2/p279/p279_064.wav|25|wiː hɐvnˌɑːt ɡˈɪvən ˌʌp hˈoʊp.
+DUMMY2/p304/p304_416.wav|72|hiː tˈʊk ˌoʊvɚɹ ˌaʊɚ lˈaɪvz.
+DUMMY2/p313/p313_119.wav|76|ˈoʊ nˈiːl ɪz ɹɪpjˈuːɾᵻd tə hæv ɹɪplˈaɪd.
+DUMMY2/p287/p287_195.wav|77|ɪt kˈʌmz fɹʌm ɹɪflˈɛkʃən ɔːɹ θˈɪŋkɪŋ.
+DUMMY2/p234/p234_008.wav|3|ðiːz tˈeɪk ðə ʃˈeɪp əvə lˈɑːŋ ɹˈaʊnd ˈɑːɹtʃ, wɪð ɪts pˈæθ hˈaɪ əbˈʌv, ænd ɪts tˈuː ˈɛndz ɐpˈæɹəntli bɪjˌɑːnd ðə hɚɹˈaɪzən.
+DUMMY2/p277/p277_119.wav|89|nˈætʃɚɹəli, ɪt wʌz nˌɑːt dˈɪfɪkəlt tə fˈaɪnd səpˈoːɹt fɔːɹ ðiːz pɹəpˈoʊzəlz.
+DUMMY2/p281/p281_394.wav|36|wˈʌt ɑːɹ ðeɪ fɔːɹ ?
+DUMMY2/p287/p287_272.wav|77|ænd ðeɪ wɜː bˌiːɪŋ pˈeɪd ?
+DUMMY2/p288/p288_071.wav|47|hiː sˈiːmd tə lˈuːz hɪz fˈoʊkəs.
+DUMMY2/p335/p335_245.wav|49|ɐ fɹˈɛndʃɪp ðæt wɪl ɛndˈʊɹ.
+DUMMY2/p239/p239_061.wav|48|ˈɔːl mˈænɚɹ ʌv pɹɪkˈɔːʃən ænd pɹətˈɛkʃən ɑːɹ tˈeɪkən.
+DUMMY2/p254/p254_003.wav|41|sˈɪks spˈuːnz ʌv fɹˈɛʃ snˈoʊ pˈiːz, fˈaɪv θˈɪk slˈæbz ʌv blˈuː tʃˈiːz, ænd mˈeɪbiː ɐ snˈæk fɔːɹ hɜː bɹˈʌðɚ bˈɑːb.
+DUMMY2/p259/p259_282.wav|7|wˈɑːʃɪŋtən ɪz kənsˈuːmd baɪ ðə kɹˈaɪsɪs.
+DUMMY2/p253/p253_202.wav|70|sˈædli, ɪt kˈænt.
+DUMMY2/p318/p318_333.wav|19|bˌʌt wɛn wiː dˈuː ɪt ɪz ɡɹˈeɪt.
+DUMMY2/p351/p351_363.wav|33|juː wɪl nˈɛvɚ fɚɡˈɛt ðə klˈʌtʃɪŋ hˈɔːɹɚ.
+DUMMY2/p241/p241_374.wav|86|ðɛɹ ɪz nˈoʊ sˈɪɡnɪtʃɚ.
+DUMMY2/p272/p272_216.wav|69|ðə ɹɪpˈoːɹt ɪz dˈuː ˈaʊt nˈɛkst mˈʌnθ.
+DUMMY2/p330/p330_355.wav|1|aɪv ɡɑːt maɪ ˈoʊn aɪdˈiəz.
+DUMMY2/p270/p270_179.wav|8|ðɪ ˈaʊtkʌm ɪz nˈaʊ ɪn ˌaʊɚɹ ˈoʊn hˈændz.
+DUMMY2/p257/p257_079.wav|105|ɪt ɪz nˌɑːt lˈɑːŋ tˈɜːm, bˌʌt ˈaɪ nˈiːd tˈaɪm tə ɹɪkˈʌvɚ.
+DUMMY2/p257/p257_027.wav|105|ðeɪ ʃˌʊdəv ɐ mˈeɪdʒɚ ɹɪθˈɪŋk ɐbˌaʊt ðɪ ɪvˈɛnt fɔːɹ nˈɛkst jˈɪɹ.
+DUMMY2/p279/p279_118.wav|25|dˈʌz ðɪs mˈiːn.
+DUMMY2/p334/p334_058.wav|38|hˈoʊpfəli, ɪt wɪl biː bˈɪlt baɪ nˈɛkst jˈɪɹ.
+DUMMY2/p363/p363_178.wav|6|ðæt wʌzɐ hjˈuːdʒ ɛkspˈiəɹɪəns.
+DUMMY2/p376/p376_227.wav|71|"ænd θˈɔːt wiː wʊd ɡɛt ɐwˈeɪ wɪð ɪt."
+DUMMY2/p330/p330_411.wav|1|juː nˈoʊ, hiː wʌz stɹˈʌɡlɪŋ wɪð hɪz ɡˈeɪm ˈɔːl wˈiːk.
+DUMMY2/p326/p326_316.wav|28|ɪt sˈɜːtənli sˈaʊndᵻd ɪt æt tˈaɪmz.
+DUMMY2/p323/p323_048.wav|34|mˈæki wʌz æt hˈoʊm, ʌnˈeɪbəl tə wˈɑːtʃ.
+DUMMY2/p313/p313_422.wav|76|nˈaʊ, ðæt ɪz ɐ ɡˈʊd dˈiːl.
+DUMMY2/p364/p364_113.wav|88|ɪt wʌz dʒˈʌst ɡɹˈeɪt.
+DUMMY2/p286/p286_414.wav|63|ɪts dʒˈʌst ɐ tɹˈeɪnɪŋ θˈɪŋ.
+DUMMY2/p288/p288_229.wav|47|haʊˈɛvɚ, nˈoʊ fˈɜːðɚɹ ˈækʃən wʌz tˈeɪkən baɪ pəlˈiːs.
+DUMMY2/p259/p259_142.wav|7|wˌʌt hˈæpənd ɪn ðæt ɡˈeɪm ?
+DUMMY2/p297/p297_118.wav|42|ɪts tˈuː bˈɪɡ ɐ ɹˈɪsk tə tˈeɪk.
+DUMMY2/p313/p313_209.wav|76|ðə nˈaɪt ɪz jˈʌŋ.
+DUMMY2/p303/p303_279.wav|44|ˈaɪ bˈɔːt ɐ kˈɑːɹ æt ˈɔːkʃən.
+DUMMY2/p345/p345_166.wav|82|mˈɪlɚ wʌz ˈɛvɹi bˈɪt æz hˈæpi.
+DUMMY2/p333/p333_289.wav|64|ɪts ɡˌoʊɪŋ təbi kwˈaɪt ɐ tʃˈælɪndʒ.
+DUMMY2/p336/p336_323.wav|98|wˈʌn pˈeɪpɚ wʌz nˌɑːt ɹɪtˈɜːnd.
+DUMMY2/p271/p271_082.wav|27|hiː ɪz ɪnðə kjˈuː.
+DUMMY2/p314/p314_175.wav|51|ðɛɹ ɪz nˈoʊ sˈʌbstɪtˌuːt.
+DUMMY2/p248/p248_124.wav|99|ˈaɪ kˈænt ˈiːvən ɡɛt ˌɪntʊ ðɪ ɐ tˈiːm.
+DUMMY2/p297/p297_160.wav|42|tˈæks ɪz ɐ mˈæɾɚ fɔːɹ nˈæʃənəl ɡˈʌvɚnmənts.
+DUMMY2/p236/p236_299.wav|75|hˌaʊ dˈuː juː ɡɛt ɪt bˈæk ?
+DUMMY2/p248/p248_300.wav|99|ɪt wˈʌznt dʒˈʌst ðə kˈæɹɪktɚ ænd ˈɛnɚdʒi ʌvðə plˈeɪɪŋ.
+DUMMY2/p231/p231_429.wav|50|hiː ɪz ɑːnðə ɹˈɔŋ sˈaɪd.
+DUMMY2/p250/p250_368.wav|24|wiː pˌʊt ˌaʊɚ bˈɪd ɪn lˈæst nˈaɪt.
+DUMMY2/p376/p376_191.wav|71|"ˈaɪ æm tˈoʊɾəli sɚpɹˈaɪzd."
+DUMMY2/p250/p250_419.wav|24|ʃiː stˈɑːɹɾᵻd tə pˌʊt ˌɑːn wˈeɪt.
+DUMMY2/p239/p239_037.wav|48|hiː wˈɜːks æt ðɪ ˈɛɹpoːɹt.
+DUMMY2/p340/p340_165.wav|74|hiː wʌz vˈɛɹi fˈɪt.
+DUMMY2/p339/p339_258.wav|18|ðɛɹˌɑːɹ nˌɑːt tˈuː mɛni lˈaɪk hˌɪm.
+DUMMY2/p326/p326_266.wav|28|ɪt mˈeɪ ˈɑːlsoʊ biː hɜː lˈæst.
+DUMMY2/p231/p231_472.wav|50|hiː fˈɛlt ɪt wʌzðə ɹˈaɪt tˈaɪm.
+DUMMY2/p261/p261_411.wav|100|ˈaɪ hɐd ɐ fˈɔːɹtʃənət wˈɔːɹ.
+DUMMY2/p272/p272_359.wav|69|nˈaʊ, ðˈoʊ, hiː hɐz ɐn ɪnsˈɛntɪv.
+DUMMY2/p340/p340_015.wav|74|ðə ɡɹˈiːks jˈuːzd tʊ ɪmˈædʒɪn ðˌɐɾɪt wʌzɐ sˈaɪn fɹʌmðə ɡˈɑːdz tə foːɹtˈɛl wˈɔːɹ ɔːɹ hˈɛvi ɹˈeɪn.
+DUMMY2/p283/p283_022.wav|95|ðɪ ˈæktʃuːəl pɹˈaɪmɚɹi ɹˈeɪnboʊ ɑːbzˈɜːvd ɪz sˈɛd təbi ðɪ ɪfˈɛkt ʌv sˈuːpɚɹɪmpəzˈɪʃən əvə nˈʌmbɚɹ ʌv bˈoʊz.
+DUMMY2/p281/p281_334.wav|36|haʊˈɛvɚ, ðə ɡɹˈuːps dɪnˈaɪd ðə klˈeɪmz.
+DUMMY2/p318/p318_223.wav|19|wiː ɹɪmˈeɪn kəmˈɪɾᵻd tʊ ɪt, æz dˈʌz ðə ɡˈʌvɚnmənt.
+DUMMY2/p281/p281_039.wav|36|ðɪs fˈɪlm wɪl biː tˈoʊɾəli ˈɔːsʌm.
+DUMMY2/p270/p270_013.wav|8|sˌʌm hæv ɐksˈɛptᵻd ɪt æz ɐ mˈɪɹəkəl wɪðˌaʊt fˈɪzɪkəl ɛksplɐnˈeɪʃən.
+DUMMY2/p243/p243_047.wav|53|haʊˈɛvɚ, ðɛɹ ɪz ɐn ˈɪʃuː, ˌɪzənt ðˈɛɹ ?
+DUMMY2/p374/p374_122.wav|11|ðə kˈoːɹs ɪz ɪn ɡɹˈeɪt kəndˈɪʃən.
+DUMMY2/p302/p302_040.wav|30|ˌɑːn fjˈuːəl, ðə tʃˈænsɛlɚ hɐz ɐ nˈʌmbɚɹ ʌv ˈɑːpʃənz.
+DUMMY2/p254/p254_231.wav|41|ænd θˈɔːt wiː wʊd ɡɛt ɐwˈeɪ wɪð ɪt.
+DUMMY2/p246/p246_222.wav|5|ɪts nˌɑːt bɪfˌoːɹ tˈaɪm.
+DUMMY2/p262/p262_044.wav|45|ɪt ɪz dˈɪfɪkəlt fɔːɹ ˈɑːli.
+DUMMY2/p270/p270_005.wav|8|ʃiː kæn skˈuːp ðiːz θˈɪŋz ˌɪntʊ θɹˈiː ɹˈɛd bˈæɡz, ænd wiː wɪl ɡˌoʊ mˈiːt hɜː wˈɛnzdeɪ æt ðə tɹˈeɪn stˈeɪʃən.
+DUMMY2/p274/p274_340.wav|32|ðɪs ɪz ɐ hɪstˈɔːɹɪk əkˈeɪʒən.
+DUMMY2/p329/p329_045.wav|103|ˈaɪ hˈoʊp juː wɪl lˈiːv ɪt æt ðˈæt.
+DUMMY2/p285/p285_188.wav|2|ˌɛni tʃˈeɪndʒ wʊd biː sˈʌbdʒɛkt tə ðə skˈɑːɾɪʃ pˈɑːɹləmənts ɐpɹˈuːvəl.
+DUMMY2/p260/p260_193.wav|81|ðə ʃˈædoʊ tʃˈænsɛlɚɹ ɪz ɐwˈeɪ ˌɑːn hˈɑːlɪdˌeɪ.
+DUMMY2/p259/p259_371.wav|7|hiː wʌz ʌnˈeɪbəl tə kˈʌm.
+DUMMY2/p275/p275_052.wav|40|sˈɛvɹəl ˈʌðɚ pjˈuːpəlz ænd stˈæf wɜː sˈiəɹɪəsli ˈɪndʒɚd ɪnðɪ ˈæksɪdənt.
+DUMMY2/p233/p233_159.wav|84|bˌʌt hiː stɹˈɛst ðætðə pˈɑːɹtnɚʃˌɪp ɪz nˌɑːɾə kənstɹˈʌkʃən kˈʌmpəni.
+DUMMY2/p277/p277_312.wav|89|ɪt wɪl wˈɜːk.
+DUMMY2/p295/p295_211.wav|92|lˈiːvɪŋ ðə lˈeɪbɚ pˈɑːɹɾi ɪz wˈʌn θˈɪŋ.
+DUMMY2/p297/p297_150.wav|42|ɪt ɪz ðə wˈɛlθɪəst ɪn jˈʊɹəp.
+DUMMY2/p305/p305_026.wav|54|hiː ˈædᵻd, haʊˈɛvɚ, ðæt ˈɔːl ˈɑːpʃənz ɑːɹ ˌʌndɚ ɹɪvjˈuː.
+DUMMY2/p292/p292_121.wav|13|ðɪs wʊd nˌɑːt biː maɪ fˈɜːst tʃˈɔɪs.
+DUMMY2/p253/p253_346.wav|70|ɪt ɪz ðə hˈɑːlɪdˌeɪ pɹˈoʊɡɹæm wɪð ɐ mˈɔːɹɡɪdʒ.
+DUMMY2/p363/p363_171.wav|6|hiː dˈɪdnt nˈoʊ wˌɛɹ tə lˈʊk.
+DUMMY2/p233/p233_128.wav|84|ɪt ɪz stˈɪl tˈuː ˈɜːli fɔːɹ ˌɛni lˈaɪkli kəntˈɛndɚz tə hæv ɪmˈɜːdʒd.
+DUMMY2/p251/p251_137.wav|9|wiː ɑːɹ kˈɜːɹəntli kənsˈʌltɪŋ wɪð ɐ wˈaɪd ɹˈeɪndʒ ʌv ˈɪntɹəstᵻd pˈɑːɹɾɪz.
+DUMMY2/p334/p334_034.wav|38|ɐpˈɔɪntᵻd dʒˈɛnɚɹəl sˈɛkɹətɹi lˈæst sɛptˈɛmbɚ.
+DUMMY2/p286/p286_225.wav|63|ðɪs wɪl tˈeɪk sˈɛvɹəl wˈiːks.
+DUMMY2/p363/p363_183.wav|6|pˈʌblɪk sˈeɪfti ɪz pˈæɹəmˌaʊnt.
+DUMMY2/p256/p256_207.wav|90|ˈæftɚ ðæt tˈaɪm, ðə mˈɑːɹkɪt ɪtsˈɛlf wɪl sˈɛt ðə pɹˈaɪsᵻz.
+DUMMY2/p273/p273_311.wav|56|dʒˈɑːb lˈɔsᵻz wɜːɹ ˈɑːlsoʊ ɐnˈaʊnst.
+DUMMY2/p274/p274_425.wav|32|ðə pɹədʒˈɛkʃənz ɑːɹ vˈɛɹi pˈɑːzɪtˌɪv fɔːɹ sˈaʊθ ˈæfɹɪkə.
+DUMMY2/p254/p254_065.wav|41|ðæts ðə dˈeɪ dʒˈɑːb.
+DUMMY2/p335/p335_123.wav|49|wˈæɡnɚ wʌz nˈɛvɚ lˈaɪk ðˈɪs.
+DUMMY2/p258/p258_105.wav|26|wiː duːnˌɑːt ɛkspˈɛkt ˌɛni sˈɜːplʌs.
+DUMMY2/p286/p286_294.wav|63|ɪt wʌz ɐn ˈiːzi dᵻsˈɪʒən tə kˈʌm hˈɪɹ.
+DUMMY2/p361/p361_218.wav|79|bˌʌt wiː wɜː ɹˈɔŋ.
+DUMMY2/p247/p247_426.wav|14|bˌiːɪŋ kˈæptɪn ʌv ðɪs klˈʌb ɪz fæntˈæstɪk.
+DUMMY2/p266/p266_391.wav|20|ɪn tˈaɪm, mˈeɪ pɹˈuːv ɐ wˈɜːði səksˈɛsɚ tə bˈɪli dˈɑːdz.
+DUMMY2/p253/p253_116.wav|70|ɪt ɪz sˌoʊ sˈæd.
+DUMMY2/p261/p261_081.wav|100|ˌaʊɚ mˈʌðɚɹ ɪz vˈɛɹi wˈʌɹɪd.
+DUMMY2/p268/p268_131.wav|87|bˌʌt ðˈɛn ðeɪ skˈoːɹd ðɛɹ fˈoːɹθ.
+DUMMY2/p229/p229_192.wav|67|ˈaɪ hæv ðə fˈɜːst sˈɪks mˈʌnθs ʌv nˈɛkst sˈiːzən tə pɹˈuːv maɪsˈɛlf.
+DUMMY2/p275/p275_260.wav|40|ðeɪ wˈɑːnt tə ʃˈʌt ðə skˈɑːɾɪʃ ˈɑːfɪs.
+DUMMY2/p313/p313_109.wav|76|nˈʌθɪŋ ɪz bˌiːɪŋ ˈɑːfɚd ɪn ɛkstʃˈeɪndʒ.
+DUMMY2/p347/p347_072.wav|46|θˈæŋkfəli, mˈɪstɚ kˈæmbəl wʌz ˈeɪbəl tə hˈɛlp.
+DUMMY2/p298/p298_334.wav|68|hˈoʊpfəli, ðə hˈoʊl ʌv skˈɑːɾɪʃ ɹˈʌɡbi wʌz pˈeɪɪŋ ɐtˈɛnʃən.
+DUMMY2/p271/p271_232.wav|27|dʒˈɪm wˈɑːlᵻs, ðə dʒˈʌstɪs mˈɪnɪstɚ, ɐknˈɑːlɪdʒd ðæt pɹˈɪzənɚ nˈʌmbɚz wɜːɹ ɐ kənsˈɜːn.
+DUMMY2/p283/p283_056.wav|95|fɚðə mˈiːntaɪm, ðˈoʊ, ðə sˈaɪnz ɑːɹ ɡˈʊd.
+DUMMY2/p255/p255_239.wav|31|ɪts ðə sˈeɪm æz ɡlˈæzɡoʊ.
+DUMMY2/p267/p267_244.wav|0|wiː hæv kˈʌm ɐ lˈɑːŋ wˈeɪ ɪnðə lˈæst fjˈuː sˈɛʃənz.
+DUMMY2/p340/p340_403.wav|74|ˈaɪ hɐd ɐ bˈɔːl tədˈeɪ.
+DUMMY2/p230/p230_083.wav|35|ɪt mˌaɪt tʃˈeɪndʒ jʊɹ lˈaɪf.
+DUMMY2/p299/p299_403.wav|58|wiː wɪl hæv tə sˈiː, bˌʌt ɪt mˌeɪks juː θˈɪŋk.
+DUMMY2/p343/p343_128.wav|21|ðˈɛn kˈeɪm ðə kɹˈʌntʃ.
+DUMMY2/p297/p297_021.wav|42|ðə dˈɪfɹəns ɪnðə ɹˈeɪnboʊ dɪpˈɛndz kənsˈɪdɚɹəbli əpˌɑːn ðə sˈaɪz ʌvðə dɹˈɑːps, ænd ðə wˈɪdθ ʌvðə kˈʌlɚd bˈænd ˈɪnkɹiːsᵻz æz ðə sˈaɪz ʌvðə dɹˈɑːps ˈɪnkɹiːsᵻz.
+DUMMY2/p298/p298_275.wav|68|ðɛɹˌɑːɹ lˈɑːts ʌv ðiːz wˈɪmɪn ɪn fˈɪnlənd.
+DUMMY2/p347/p347_286.wav|46|ɪt ɪz dʒˈʌst tˈuː lˈɑːŋ sˈɪns ðə wˈɔːɹ.
+DUMMY2/p239/p239_445.wav|48|ˈiːðɚ ɡɹˈuːp ɪz lˈɪvɪŋ ɪn fˈæntəsi lˈænd.
+DUMMY2/p286/p286_003.wav|63|sˈɪks spˈuːnz ʌv fɹˈɛʃ snˈoʊ pˈiːz, fˈaɪv θˈɪk slˈæbz ʌv blˈuː tʃˈiːz, ænd mˈeɪbiː ɐ snˈæk fɔːɹ hɜː bɹˈʌðɚ bˈɑːb.
+DUMMY2/p299/p299_082.wav|58|ˈaɪ stˈɪl fˈiːl lˈaɪk ɐ wˈiː bˈɔɪ.
+DUMMY2/p306/p306_213.wav|12|ɪt ɪz lˈaɪk bˌiːɪŋ ɐ kwˈɑːlɪfˌaɪɚɹ ɐɡˈɛn.
+DUMMY2/p339/p339_305.wav|18|wiː nˈoʊ ðə ɡˈoʊlz wɪl kˈʌm.
+DUMMY2/p265/p265_274.wav|73|ðɪs tˈaɪm, fɔːɹ ɹˈeɪndʒɚz, ɪt ɪz sˈɜːtənli ðə lˈæɾɚ.
+DUMMY2/p310/p310_382.wav|17|ɪt hɐz ðə bˈæŋk ʌv skˈɑːtlənd bɪhˈaɪnd ɪt.
+DUMMY2/p335/p335_403.wav|49|ˈɛnɪwˌeɪ, ˈiːvən ɪf ðeɪ dˈɪdnt ɪt wˌʊdəntəv mˈæɾɚd.
+DUMMY2/p246/p246_330.wav|5|ˈaɪ wʊd biː kwˈaɪt hˈæpi fɚðə mˈʌni təbi ɡˈɪvən bˈæk.
+DUMMY2/p288/p288_386.wav|47|ðɛɹ ɪz ɐ səlˈuːʃən, ʃiː bɪlˈiːvz.
+DUMMY2/p234/p234_019.wav|3|sˈɪns ðˈɛn fˈɪzɪsˌɪsts hæv fˈaʊnd ðˌɐɾɪt ɪz nˌɑːt ɹɪflˈɛkʃən, bˌʌt ɹɪfɹˈækʃən baɪ ðə ɹˈeɪndɹɑːps wˌɪtʃ kˈɔːzᵻz ðə ɹˈeɪnboʊz.
+DUMMY2/p287/p287_408.wav|77|fˈɜːst, wiː hɐd ðə bˈæɾəl ʌv bɹˈɪtən.
+DUMMY2/p286/p286_249.wav|63|ʃiː wɪl ɐtˈɛnd ɪn dʒuːlˈaɪ.
+DUMMY2/p251/p251_235.wav|9|aɪd nˈɛvɚ sˈiːn ɐ plˈeɪ ɐbˈaʊt mˌiː.
+DUMMY2/p347/p347_291.wav|46|ɪnʃˈʊɹəns wɪl biː kˈʌvɚd baɪ ðə ɹɪsˈiːvɪŋ ɡˈælɚɹiz.
+DUMMY2/p257/p257_058.wav|105|ɪt ɪz nˌɑːt ɡɹˈeɪt ˈɑːɹt.
+DUMMY2/p231/p231_471.wav|50|dˈɛnᵻs wʌz nˌɑːt sˌoʊ ʃˈʊɹ.
+DUMMY2/p341/p341_107.wav|66|ðɛɹwˌʌz ɡɹˈeɪt səpˈoːɹt ˈɔːl ɹˈaʊnd ðə ɹˈaʊt.
+DUMMY2/p264/p264_160.wav|65|ɪt wʌz klˈɪɹli nˌɑːɾə bˈæɾəl.
+DUMMY2/p252/p252_155.wav|55|ˈaɪ θˈɪŋk, ðˈɛɹfoːɹ ˈaɪ æm ?
+DUMMY2/p336/p336_264.wav|98|fˈɜːɡəsən mˈʌst tˈeɪk ðə blˈeɪm.
+DUMMY2/p274/p274_142.wav|32|ðə ɹˌɛfɚɹˈiː fˈeɪsᵻz ɐ mˈæsɪv dʒˈɑːb.
+DUMMY2/p303/p303_005.wav|44|ʃiː kæn skˈuːp ðiːz θˈɪŋz ˌɪntʊ θɹˈiː ɹˈɛd bˈæɡz, ænd wiː wɪl ɡˌoʊ mˈiːt hɜː wˈɛnzdeɪ æt ðə tɹˈeɪn stˈeɪʃən.
+DUMMY2/p233/p233_240.wav|84|ðə sˈɪŋɚɹ ɪz ɛkspˈɛktᵻd təbi ɪn hˈɑːspɪɾəl fɔːɹ sˈɛvɹəl dˈeɪz.
+DUMMY2/p333/p333_220.wav|64|ðɪs pɹˈɑːsɛs ʌv ɐtɹˈɪʃən ɪz ɛkspˈɛktᵻd tə kəntˈɪnjuː.
+DUMMY2/p285/p285_303.wav|2|ˈælɪks smˈɪθ hɐzbɪn ɐ mˈæsɪv ˈɪnfluːəns ˌɑːn maɪ kɚɹˈɪɹ æz wˈɛl.
+DUMMY2/p277/p277_348.wav|89|tə dˈuː sˌoʊ hiː ɹˈɛkənz ðˌæɾə ɡˈʊd ˈoʊpənɪŋ ɹɪzˈʌlt ɪz ɪsˈɛnʃəl.
+DUMMY2/p311/p311_290.wav|4|ˈaɪ æm nˌɑːt ɪn dɪnˈaɪəl.
+DUMMY2/p286/p286_316.wav|63|ˈaɪ æm ɐ ɹˈiːteɪlɚ baɪ nˈeɪtʃɚ.
+DUMMY2/p306/p306_119.wav|12|kəmplˈiːʃən ɪz ɛkspˈɛktᵻd baɪ ɑːktˈoʊbɚ ðə fˈɑːloʊɪŋ jˈɪɹ.
+DUMMY2/p240/p240_028.wav|93|ɪz ðɪs ˈækjʊɹət?
+DUMMY2/p238/p238_295.wav|37|ɪt hɐzbɪn ɹɪkˈoːɹdᵻd twˈaɪs.
+DUMMY2/p278/p278_049.wav|10|hiː wɪl nˈiːd ðæt məʃˈiːn.
+DUMMY2/p351/p351_282.wav|33|wiː dʒˈʌst wˈɪʃ ðeɪ hɐd dˈʌn sˌoʊ bɪfˈoːɹ.
+DUMMY2/p267/p267_348.wav|0|mˈɛnɪəv ðiːz pɹˈɑːpɚɾɪz ɑːɹ loʊkˈeɪɾᵻd ɪnðə sˈaʊθ ʌv ˈɪŋɡlənd.
+DUMMY2/p312/p312_360.wav|62|ænd skˈɑːtlənd ɪz nˈoʊ dˈɪfɹənt.
+DUMMY2/p311/p311_324.wav|4|hiː pɹɪtˈɛndᵻd nˌɑːt tə kˈɛɹ.
+DUMMY2/p283/p283_389.wav|95|skɹˈuːtɪni baɪ ðə jˌʊɹəpˈiən pˈɑːɹləmənt ɪz lˈɪmɪɾᵻd.
+DUMMY2/p266/p266_079.wav|20|hiː ɪz ɪnðə kjˈuː.
+DUMMY2/p274/p274_424.wav|32|nˌɑːt ðæt skˈɑːtlənd kæn klˈeɪm ðə mˈɔːɹəl hˈaɪ ɡɹˈaʊnd.
+DUMMY2/p303/p303_169.wav|44|fɔːɹ ˈæθliːts ɪn ˌaʊɚ kˈɜːɹənt klˈaɪmət, ðɛɹ spˈoːɹt ɪz ðɛɹ lˈaɪvlihˌʊd.
+DUMMY2/p252/p252_237.wav|55|juː nˈoʊ ðə tˈaɪp.
+DUMMY2/p323/p323_115.wav|34|pˈɑːɹts ʌvðə sˈɪstəm ɑːɹ ɔːlɹˌɛdi ˌoʊvɚstɹˈɛtʃt.
+DUMMY2/p361/p361_013.wav|79|sˌʌm hæv ɐksˈɛptᵻd ɪt æz ɐ mˈɪɹəkəl wɪðˌaʊt fˈɪzɪkəl ɛksplɐnˈeɪʃən.
+DUMMY2/p333/p333_356.wav|64|wˌɪtʃ hiː kæn dˈuː.
+DUMMY2/p241/p241_029.wav|86|haʊˈɛvɚ, ðə fˈɑːloʊɪŋ jˈɪɹ ðə kˈænsɚ ɹɪtˈɜːnd.
+DUMMY2/p248/p248_371.wav|99|wˈɛðɚ hɪz stˈæns ɪz ʃˈɛɹd baɪ ðɪ ˈɪnkʌmˌɪŋ mˈænɪdʒɚɹ ɪz ɐnˈʌðɚ mˈæɾɚ.
+DUMMY2/p260/p260_007.wav|81|ðə ɹˈeɪnboʊ ɪz ɐ dɪvˈɪʒən ʌv wˈaɪt lˈaɪt ˌɪntʊ mˈɛni bjˈuːɾɪfəl kˈʌlɚz.
+DUMMY2/p287/p287_257.wav|77|ðə kənsˈɜːnz ɑːɹ ðə sˈeɪm.
+DUMMY2/p263/p263_125.wav|39|ɪt ˌɪzənt ɐ hˈæpi mˈɛmɚɹi.
+DUMMY2/p277/p277_258.wav|89|ɪmˈiːdɪət ˈækʃən mˈʌst biː tˈeɪkən.
+DUMMY2/p363/p363_219.wav|6|ɪt wʌz ɪmpˈoːɹtənt ɪn tɹˈeɪnɪŋ tˈɜːmz.
+DUMMY2/p269/p269_191.wav|94|maɪ mˈeɪn kənsˈɜːn ɪz ðæt pˈʌblɪk hˈɛlθ ɪz nˌɑːt pˌʊt æt ɹˈɪsk.
+DUMMY2/p262/p262_020.wav|45|mˈɛni kˈɑːmplᵻkˌeɪɾᵻd aɪdˈiəz ɐbˌaʊt ðə ɹˈeɪnboʊ hɐvbɪn fˈɔːɹmd.
+DUMMY2/p273/p273_023.wav|56|ɪf ðə ɹˈɛd ʌvðə sˈɛkənd bˈoʊ fˈɔːlz əpˌɑːn ðə ɡɹˈiːn ʌvðə fˈɜːst, ðə ɹɪzˈʌlt ɪz tə ɡˈɪv ɐ bˈoʊ wɪð ɐn ɐbnˈoːɹməli wˈaɪd jˈɛloʊ bˈænd, sˈɪns ɹˈɛd ænd ɡɹˈiːn lˈaɪt wɛn mˈɪkst fˈɔːɹm jˈɛloʊ.
+DUMMY2/p278/p278_029.wav|10|ðeɪ hæv nˈaʊ bˌɪn bˈænd fɹʌm kˈɛltɪk pˈɑːɹk fɔːɹ lˈaɪf.
+DUMMY2/p310/p310_065.wav|17|ˈaɪ hæv hɐd nˈoʊ sˈoʊʃəl lˈaɪf æt ˈɔːl.
+DUMMY2/p255/p255_352.wav|31|hiːz vˈɛɹi ɛksplˈoʊsɪv.
+DUMMY2/p376/p376_019.wav|71|"sˈɪns ðˈɛn fˈɪzɪsˌɪsts hæv fˈaʊnd ðˌɐɾɪt ɪz nˌɑːt ɹɪflˈɛkʃən, bˌʌt ɹɪfɹˈækʃən baɪ ðə ɹˈeɪndɹɑːps wˌɪtʃ kˈɔːzᵻz ðə ɹˈeɪnboʊz. "
+DUMMY2/p263/p263_307.wav|39|ɪz ðɛɹ ɐ wˈeɪɾɪŋ lˈɪst ?
+DUMMY2/p249/p249_258.wav|80|ðeɪ mˈʌst plˈeɪ fɔːɹ ˈiːtʃ ˈʌðɚ.
+DUMMY2/p258/p258_111.wav|26|mˈeɪbiː ðɪs bˈæɾəl hɐzbɪn.
+DUMMY2/p316/p316_129.wav|85|ðɛɹ kæn biː nˈoʊ kˈɑːmpɹəmˌaɪz ˌɑːn ðæt dɪmˈænd.

filelists/vctk_audio_sid_text_val_filelist.txt

+DUMMY2/p364/p364_240.wav|88|It had happened to him.
+DUMMY2/p280/p280_148.wav|52|It is open season on the Old Firm.
+DUMMY2/p231/p231_320.wav|50|However, he is a coach, and he remains a coach at heart.
+DUMMY2/p282/p282_129.wav|83|It is not a U-turn.
+DUMMY2/p254/p254_015.wav|41|The Greeks used to imagine that it was a sign from the gods to foretell war or heavy rain.
+DUMMY2/p228/p228_285.wav|57|The songs are just so good.
+DUMMY2/p334/p334_307.wav|38|If they don't, they can expect their funding to be cut.
+DUMMY2/p287/p287_081.wav|77|I've never seen anything like it.
+DUMMY2/p247/p247_083.wav|14|It is a job creation scheme.)
+DUMMY2/p264/p264_051.wav|65|We were leading by two goals.)
+DUMMY2/p335/p335_058.wav|49|Let's see that increase over the years.
+DUMMY2/p236/p236_225.wav|75|There is no quick fix.
+DUMMY2/p374/p374_353.wav|11|And that brings us to the point.
+DUMMY2/p272/p272_076.wav|69|Sounds like The Sixth Sense?
+DUMMY2/p271/p271_152.wav|27|The petition was formally presented at Downing Street yesterday.
+DUMMY2/p228/p228_127.wav|57|They've got to account for it.
+DUMMY2/p276/p276_223.wav|106|It's been a humbling year.
+DUMMY2/p262/p262_248.wav|45|The project has already secured the support of Sir Sean Connery.
+DUMMY2/p314/p314_086.wav|51|The team this year is going places.
+DUMMY2/p225/p225_038.wav|101|Diving is no part of football.
+DUMMY2/p279/p279_088.wav|25|The shareholders will vote to wind up the company on Friday morning.
+DUMMY2/p272/p272_018.wav|69|Aristotle thought that the rainbow was caused by reflection of the sun's rays by the rain.
+DUMMY2/p256/p256_098.wav|90|She told The Herald.
+DUMMY2/p261/p261_218.wav|100|All will be revealed in due course.
+DUMMY2/p265/p265_063.wav|73|IT shouldn't come as a surprise, but it does.
+DUMMY2/p314/p314_042.wav|51|It is all about people being assaulted, abused.
+DUMMY2/p241/p241_188.wav|86|I wish I could say something.
+DUMMY2/p283/p283_111.wav|95|It's good to have a voice.
+DUMMY2/p275/p275_006.wav|40|When the sunlight strikes raindrops in the air, they act as a prism and form a rainbow.
+DUMMY2/p228/p228_092.wav|57|Today I couldn't run on it.
+DUMMY2/p295/p295_343.wav|92|The atmosphere is businesslike.
+DUMMY2/p228/p228_187.wav|57|They will run a mile.
+DUMMY2/p294/p294_317.wav|104|It didn't put me off.
+DUMMY2/p231/p231_445.wav|50|It sounded like a bomb.
+DUMMY2/p272/p272_086.wav|69|Today she has been released.
+DUMMY2/p255/p255_210.wav|31|It was worth a photograph.
+DUMMY2/p229/p229_060.wav|67|And a film maker was born.
+DUMMY2/p260/p260_232.wav|81|The Home Office would not release any further details about the group.
+DUMMY2/p245/p245_025.wav|59|Johnson was pretty low.
+DUMMY2/p333/p333_185.wav|64|This area is perfect for children.
+DUMMY2/p244/p244_242.wav|78|He is a man of the people.
+DUMMY2/p376/p376_187.wav|71|"It is a terrible loss."
+DUMMY2/p239/p239_156.wav|48|It is a good lifestyle.
+DUMMY2/p307/p307_037.wav|22|He released a half-dozen solo albums.
+DUMMY2/p305/p305_185.wav|54|I am not even thinking about that.
+DUMMY2/p272/p272_081.wav|69|It was magic.
+DUMMY2/p302/p302_297.wav|30|I'm trying to stay open on that.
+DUMMY2/p275/p275_320.wav|40|We are in the end game.
+DUMMY2/p239/p239_231.wav|48|Then we will face the Danish champions.
+DUMMY2/p268/p268_301.wav|87|It was only later that the condition was diagnosed.
+DUMMY2/p336/p336_088.wav|98|They failed to reach agreement yesterday.
+DUMMY2/p278/p278_255.wav|10|They made such decisions in London.
+DUMMY2/p361/p361_132.wav|79|That got me out.
+DUMMY2/p307/p307_146.wav|22|You hope he prevails.
+DUMMY2/p244/p244_147.wav|78|They could not ignore the will of parliament, he claimed.
+DUMMY2/p294/p294_283.wav|104|This is our unfinished business.
+DUMMY2/p283/p283_300.wav|95|I would have the hammer in the crowd.
+DUMMY2/p239/p239_079.wav|48|I can understand the frustrations of our fans.
+DUMMY2/p264/p264_009.wav|65|There is , according to legend, a boiling pot of gold at one end. )
+DUMMY2/p307/p307_348.wav|22|He did not oppose the divorce.
+DUMMY2/p304/p304_308.wav|72|We are the gateway to justice.
+DUMMY2/p281/p281_056.wav|36|None has ever been found.
+DUMMY2/p267/p267_158.wav|0|We were given a warm and friendly reception.
+DUMMY2/p300/p300_169.wav|102|Who do these people think they are?
+DUMMY2/p276/p276_177.wav|106|They exist in name alone.
+DUMMY2/p228/p228_245.wav|57|It is a policy which has the full support of the minister.
+DUMMY2/p300/p300_303.wav|102|I'm wondering what you feel about the youngest.
+DUMMY2/p362/p362_247.wav|15|This would give Scotland around eight members.
+DUMMY2/p326/p326_031.wav|28|United were in control without always being dominant.
+DUMMY2/p361/p361_288.wav|79|I did not think it was very proper.
+DUMMY2/p286/p286_145.wav|63|Tiger is not the norm.
+DUMMY2/p234/p234_071.wav|3|She did that for the rest of her life.
+DUMMY2/p263/p263_296.wav|39|The decision was announced at its annual conference in Dunfermline.
+DUMMY2/p323/p323_228.wav|34|She became a heroine of my childhood.
+DUMMY2/p280/p280_346.wav|52|It was a bit like having children.
+DUMMY2/p333/p333_080.wav|64|But the tragedy did not stop there.
+DUMMY2/p226/p226_268.wav|43|That decision is for the British Parliament and people.
+DUMMY2/p362/p362_314.wav|15|Is that right?
+DUMMY2/p240/p240_047.wav|93|It is so sad.
+DUMMY2/p250/p250_207.wav|24|You could feel the heat.
+DUMMY2/p273/p273_176.wav|56|Neither side would reveal the details of the offer.
+DUMMY2/p316/p316_147.wav|85|And frankly, it's been a while.
+DUMMY2/p265/p265_047.wav|73|It is unique.
+DUMMY2/p336/p336_353.wav|98|Sometimes you get them, sometimes you don't.
+DUMMY2/p230/p230_376.wav|35|This hasn't happened in a vacuum.
+DUMMY2/p308/p308_209.wav|107|There is great potential on this river.
+DUMMY2/p250/p250_442.wav|24|We have not yet received a letter from the Irish.
+DUMMY2/p260/p260_037.wav|81|It's a fact.
+DUMMY2/p299/p299_345.wav|58|We're very excited and challenged by the project.
+DUMMY2/p269/p269_218.wav|94|A Grampian Police spokesman said.
+DUMMY2/p306/p306_014.wav|12|To the Hebrews it was a token that there would be no more universal floods.
+DUMMY2/p271/p271_292.wav|27|It's a record label, not a form of music.
+DUMMY2/p247/p247_225.wav|14|I am considered a teenager.)
+DUMMY2/p294/p294_094.wav|104|It should be a condition of employment.
+DUMMY2/p269/p269_031.wav|94|Is this accurate?
+DUMMY2/p275/p275_116.wav|40|It's not fair.
+DUMMY2/p265/p265_006.wav|73|When the sunlight strikes raindrops in the air, they act as a prism and form a rainbow.
+DUMMY2/p285/p285_072.wav|2|Mr Irvine said Mr Rafferty was now in good spirits.
+DUMMY2/p270/p270_167.wav|8|We did what we had to do.
+DUMMY2/p360/p360_397.wav|60|It is a relief.

filelists/vctk_audio_sid_text_val_filelist.txt.cleaned

+DUMMY2/p364/p364_240.wav|88|ɪt hɐd hˈæpənd tə hˌɪm.
+DUMMY2/p280/p280_148.wav|52|ɪt ɪz ˈoʊpən sˈiːzən ɑːnðɪ ˈoʊld fˈɜːm.
+DUMMY2/p231/p231_320.wav|50|haʊˈɛvɚ, hiː ɪz ɐ kˈoʊtʃ, ænd hiː ɹɪmˈeɪnz ɐ kˈoʊtʃ æt hˈɑːɹt.
+DUMMY2/p282/p282_129.wav|83|ɪt ɪz nˌɑːɾə jˈuːtˈɜːn.
+DUMMY2/p254/p254_015.wav|41|ðə ɡɹˈiːks jˈuːzd tʊ ɪmˈædʒɪn ðˌɐɾɪt wʌzɐ sˈaɪn fɹʌmðə ɡˈɑːdz tə foːɹtˈɛl wˈɔːɹ ɔːɹ hˈɛvi ɹˈeɪn.
+DUMMY2/p228/p228_285.wav|57|ðə sˈɔŋz ɑːɹ dʒˈʌst sˌoʊ ɡˈʊd.
+DUMMY2/p334/p334_307.wav|38|ɪf ðeɪ dˈoʊnt, ðeɪ kæn ɛkspˈɛkt ðɛɹ fˈʌndɪŋ təbi kˈʌt.
+DUMMY2/p287/p287_081.wav|77|aɪv nˈɛvɚ sˈiːn ˈɛnɪθˌɪŋ lˈaɪk ɪt.
+DUMMY2/p247/p247_083.wav|14|ɪt ɪz ɐ dʒˈɑːb kɹiːˈeɪʃən skˈiːm.
+DUMMY2/p264/p264_051.wav|65|wiː wɜː lˈiːdɪŋ baɪ tˈuː ɡˈoʊlz.
+DUMMY2/p335/p335_058.wav|49|lˈɛts sˈiː ðæt ˈɪnkɹiːs ˌoʊvɚ ðə jˈɪɹz.
+DUMMY2/p236/p236_225.wav|75|ðɛɹ ɪz nˈoʊ kwˈɪk fˈɪks.
+DUMMY2/p374/p374_353.wav|11|ænd ðæt bɹˈɪŋz ˌʌs tə ðə pˈɔɪnt.
+DUMMY2/p272/p272_076.wav|69|sˈaʊndz lˈaɪk ðə sˈɪksθ sˈɛns?
+DUMMY2/p271/p271_152.wav|27|ðə pətˈɪʃən wʌz fˈɔːɹməli pɹɪzˈɛntᵻd æt dˈaʊnɪŋ stɹˈiːt jˈɛstɚdˌeɪ.
+DUMMY2/p228/p228_127.wav|57|ðeɪv ɡɑːt tʊ ɐkˈaʊnt fɔːɹ ɪt.
+DUMMY2/p276/p276_223.wav|106|ɪts bˌɪn ɐ hˈʌmblɪŋ jˈɪɹ.
+DUMMY2/p262/p262_248.wav|45|ðə pɹˈɑːdʒɛkt hɐz ɔːlɹˌɛdi sɪkjˈʊɹd ðə səpˈoːɹt ʌv sˌɜː ʃˈɔːn kɑːnɚɹi.
+DUMMY2/p314/p314_086.wav|51|ðə tˈiːm ðɪs jˈɪɹ ɪz ɡˌoʊɪŋ plˈeɪsᵻz.
+DUMMY2/p225/p225_038.wav|101|dˈaɪvɪŋ ɪz nˈoʊ pˈɑːɹt ʌv fˈʊtbɔːl.
+DUMMY2/p279/p279_088.wav|25|ðə ʃˈɛɹhoʊldɚz wɪl vˈoʊt tə wˈaɪnd ˈʌp ðə kˈʌmpəni ˌɑːn fɹˈaɪdeɪ mˈɔːɹnɪŋ.
+DUMMY2/p272/p272_018.wav|69|ˈæɹɪstˌɑːɾəl θˈɔːt ðætðə ɹˈeɪnboʊ wʌz kˈɔːzd baɪ ɹɪflˈɛkʃən ʌvðə sˈʌnz ɹˈeɪz baɪ ðə ɹˈeɪn.
+DUMMY2/p256/p256_098.wav|90|ʃiː tˈoʊld ðə hˈɛɹəld.
+DUMMY2/p261/p261_218.wav|100|ˈɔːl wɪl biː ɹɪvˈiːld ɪn dˈuː kˈoːɹs.
+DUMMY2/p265/p265_063.wav|73|ɪt ʃˌʊdənt kˈʌm æz ɐ sɚpɹˈaɪz, bˌʌt ɪt dˈʌz.
+DUMMY2/p314/p314_042.wav|51|ɪt ɪz ˈɔːl ɐbˌaʊt pˈiːpəl bˌiːɪŋ ɐsˈɑːltᵻd, ɐbjˈuːsd.
+DUMMY2/p241/p241_188.wav|86|ˈaɪ wˈɪʃ ˈaɪ kʊd sˈeɪ sˈʌmθɪŋ.
+DUMMY2/p283/p283_111.wav|95|ɪts ɡˈʊd tə hæv ɐ vˈɔɪs.
+DUMMY2/p275/p275_006.wav|40|wˌɛn ðə sˈʌnlaɪt stɹˈaɪks ɹˈeɪndɹɑːps ɪnðɪ ˈɛɹ, ðeɪ ˈækt æz ɐ pɹˈɪzəm ænd fˈɔːɹm ɐ ɹˈeɪnboʊ.
+DUMMY2/p228/p228_092.wav|57|tədˈeɪ ˈaɪ kˌʊdənt ɹˈʌn ˈɑːn ɪt.
+DUMMY2/p295/p295_343.wav|92|ðɪ ˈætməsfˌɪɹ ɪz bˈɪznəslˌaɪk.
+DUMMY2/p228/p228_187.wav|57|ðeɪ wɪl ɹˈʌn ɐ mˈaɪl.
+DUMMY2/p294/p294_317.wav|104|ɪt dˈɪdnt pˌʊt mˌiː ˈɔf.
+DUMMY2/p231/p231_445.wav|50|ɪt sˈaʊndᵻd lˈaɪk ɐ bˈɑːm.
+DUMMY2/p272/p272_086.wav|69|tədˈeɪ ʃiː hɐzbɪn ɹɪlˈiːsd.
+DUMMY2/p255/p255_210.wav|31|ɪt wʌz wˈɜːθ ɐ fˈoʊɾəɡɹˌæf.
+DUMMY2/p229/p229_060.wav|67|ænd ɐ fˈɪlm mˈeɪkɚ wʌz bˈɔːɹn.
+DUMMY2/p260/p260_232.wav|81|ðə hˈoʊm ˈɑːfɪs wʊd nˌɑːt ɹɪlˈiːs ˌɛni fˈɜːðɚ diːtˈeɪlz ɐbˌaʊt ðə ɡɹˈuːp.
+DUMMY2/p245/p245_025.wav|59|dʒˈɑːnsən wʌz pɹˈɪɾi lˈoʊ.
+DUMMY2/p333/p333_185.wav|64|ðɪs ˈɛɹiə ɪz pˈɜːfɛkt fɔːɹ tʃˈɪldɹən.
+DUMMY2/p244/p244_242.wav|78|hiː ɪz ɐ mˈæn ʌvðə pˈiːpəl.
+DUMMY2/p376/p376_187.wav|71|"ɪt ɪz ɐ tˈɛɹəbəl lˈɔs."
+DUMMY2/p239/p239_156.wav|48|ɪt ɪz ɐ ɡˈʊd lˈaɪfstaɪl.
+DUMMY2/p307/p307_037.wav|22|hiː ɹɪlˈiːsd ɐ hˈæfdˈʌzən sˈoʊloʊ ˈælbəmz.
+DUMMY2/p305/p305_185.wav|54|ˈaɪ æm nˌɑːt ˈiːvən θˈɪŋkɪŋ ɐbˌaʊt ðˈæt.
+DUMMY2/p272/p272_081.wav|69|ɪt wʌz mˈædʒɪk.
+DUMMY2/p302/p302_297.wav|30|aɪm tɹˈaɪɪŋ tə stˈeɪ ˈoʊpən ˌɑːn ðˈæt.
+DUMMY2/p275/p275_320.wav|40|wiː ɑːɹ ɪnðɪ ˈɛnd ɡˈeɪm.
+DUMMY2/p239/p239_231.wav|48|ðˈɛn wiː wɪl fˈeɪs ðə dˈeɪnɪʃ tʃˈæmpiənz.
+DUMMY2/p268/p268_301.wav|87|ɪt wʌz ˈoʊnli lˈeɪɾɚ ðætðə kəndˈɪʃən wʌz dˌaɪəɡnˈoʊzd.
+DUMMY2/p336/p336_088.wav|98|ðeɪ fˈeɪld tə ɹˈiːtʃ ɐɡɹˈiːmənt jˈɛstɚdˌeɪ.
+DUMMY2/p278/p278_255.wav|10|ðeɪ mˌeɪd sˈʌtʃ dᵻsˈɪʒənz ɪn lˈʌndən.
+DUMMY2/p361/p361_132.wav|79|ðæt ɡɑːt mˌiː ˈaʊt.
+DUMMY2/p307/p307_146.wav|22|juː hˈoʊp hiː pɹɪvˈeɪlz.
+DUMMY2/p244/p244_147.wav|78|ðeɪ kʊd nˌɑːt ɪɡnˈoːɹ ðə wɪl ʌv pˈɑːɹləmənt, hiː klˈeɪmd.
+DUMMY2/p294/p294_283.wav|104|ðɪs ɪz ˌaʊɚɹ ʌnfˈɪnɪʃt bˈɪznəs.
+DUMMY2/p283/p283_300.wav|95|ˈaɪ wʊdhɐv ðə hˈæmɚɹ ɪnðə kɹˈaʊd.
+DUMMY2/p239/p239_079.wav|48|ˈaɪ kæn ˌʌndɚstˈænd ðə fɹʌstɹˈeɪʃənz ʌv ˌaʊɚ fˈænz.
+DUMMY2/p264/p264_009.wav|65|ðɛɹˈɪz , ɐkˈoːɹdɪŋ tə lˈɛdʒənd, ɐ bˈɔɪlɪŋ pˈɑːt ʌv ɡˈoʊld æt wˈʌn ˈɛnd. 
+DUMMY2/p307/p307_348.wav|22|hiː dɪdnˌɑːt əpˈoʊz ðə dɪvˈoːɹs.
+DUMMY2/p304/p304_308.wav|72|wiː ɑːɹ ðə ɡˈeɪtweɪ tə dʒˈʌstɪs.
+DUMMY2/p281/p281_056.wav|36|nˈʌn hɐz ˈɛvɚ bˌɪn fˈaʊnd.
+DUMMY2/p267/p267_158.wav|0|wiː wɜː ɡˈɪvən ɐ wˈɔːɹm ænd fɹˈɛndli ɹɪsˈɛpʃən.
+DUMMY2/p300/p300_169.wav|102|hˌuː dˈuː ðiːz pˈiːpəl θˈɪŋk ðeɪ ɑːɹ?
+DUMMY2/p276/p276_177.wav|106|ðeɪ ɛɡzˈɪst ɪn nˈeɪm ɐlˈoʊn.
+DUMMY2/p228/p228_245.wav|57|ɪt ɪz ɐ pˈɑːlɪsi wˌɪtʃ hɐz ðə fˈʊl səpˈoːɹt ʌvðə mˈɪnɪstɚ.
+DUMMY2/p300/p300_303.wav|102|aɪm wˈʌndɚɹɪŋ wˌʌt juː fˈiːl ɐbˌaʊt ðə jˈʌŋɡəst.
+DUMMY2/p362/p362_247.wav|15|ðɪs wʊd ɡˈɪv skˈɑːtlənd ɐɹˈaʊnd ˈeɪt mˈɛmbɚz.
+DUMMY2/p326/p326_031.wav|28|juːnˈaɪɾᵻd wɜːɹ ɪn kəntɹˈoʊl wɪðˌaʊt ˈɔːlweɪz bˌiːɪŋ dˈɑːmɪnənt.
+DUMMY2/p361/p361_288.wav|79|ˈaɪ dɪdnˌɑːt θˈɪŋk ɪt wʌz vˈɛɹi pɹˈɑːpɚ.
+DUMMY2/p286/p286_145.wav|63|tˈaɪɡɚɹ ɪz nˌɑːt ðə nˈɔːɹm.
+DUMMY2/p234/p234_071.wav|3|ʃiː dˈɪd ðæt fɚðə ɹˈɛst ʌv hɜː lˈaɪf.
+DUMMY2/p263/p263_296.wav|39|ðə dᵻsˈɪʒən wʌz ɐnˈaʊnst æt ɪts ˈænjuːəl kˈɑːnfɹəns ɪn dˈʌnfɚmlˌaɪn.
+DUMMY2/p323/p323_228.wav|34|ʃiː bɪkˌeɪm ɐ hˈɛɹoʊˌɪn ʌv maɪ tʃˈaɪldhʊd.
+DUMMY2/p280/p280_346.wav|52|ɪt wʌzɐ bˈɪt lˈaɪk hˌævɪŋ tʃˈɪldɹən.
+DUMMY2/p333/p333_080.wav|64|bˌʌt ðə tɹˈædʒədi dɪdnˌɑːt stˈɑːp ðˈɛɹ.
+DUMMY2/p226/p226_268.wav|43|ðæt dᵻsˈɪʒən ɪz fɚðə bɹˈɪɾɪʃ pˈɑːɹləmənt ænd pˈiːpəl.
+DUMMY2/p362/p362_314.wav|15|ɪz ðæt ɹˈaɪt?
+DUMMY2/p240/p240_047.wav|93|ɪt ɪz sˌoʊ sˈæd.
+DUMMY2/p250/p250_207.wav|24|juː kʊd fˈiːl ðə hˈiːt.
+DUMMY2/p273/p273_176.wav|56|nˈiːðɚ sˈaɪd wʊd ɹɪvˈiːl ðə diːtˈeɪlz ʌvðɪ ˈɑːfɚ.
+DUMMY2/p316/p316_147.wav|85|ænd fɹˈæŋkli, ɪts bˌɪn ɐ wˈaɪl.
+DUMMY2/p265/p265_047.wav|73|ɪt ɪz juːnˈiːk.
+DUMMY2/p336/p336_353.wav|98|sˈʌmtaɪmz juː ɡˈɛt ðˌɛm, sˈʌmtaɪmz juː dˈoʊnt.
+DUMMY2/p230/p230_376.wav|35|ðɪs hˈæzənt hˈæpənd ɪn ɐ vˈækjuːm.
+DUMMY2/p308/p308_209.wav|107|ðɛɹ ɪz ɡɹˈeɪt pətˈɛnʃəl ˌɑːn ðɪs ɹˈɪvɚ.
+DUMMY2/p250/p250_442.wav|24|wiː hɐvnˌɑːt jˈɛt ɹɪsˈiːvd ɐ lˈɛɾɚ fɹʌmðɪ ˈaɪɹɪʃ.
+DUMMY2/p260/p260_037.wav|81|ɪts ɐ fˈækt.
+DUMMY2/p299/p299_345.wav|58|wɪɹ vˈɛɹi ɛksˈaɪɾᵻd ænd tʃˈælɪndʒd baɪ ðə pɹˈɑːdʒɛkt.
+DUMMY2/p269/p269_218.wav|94|ɐ ɡɹˈæmpiən pəlˈiːs spˈoʊksmən sˈɛd.
+DUMMY2/p306/p306_014.wav|12|tə ðə hˈiːbɹuːz ɪt wʌzɐ tˈoʊkən ðæt ðɛɹ wʊd biː nˈoʊmˌoːɹ jˌuːnɪvˈɜːsəl flˈʌdz.
+DUMMY2/p271/p271_292.wav|27|ɪts ɐ ɹˈɛkɚd lˈeɪbəl, nˌɑːɾə fˈɔːɹm ʌv mjˈuːzɪk.
+DUMMY2/p247/p247_225.wav|14|ˈaɪ æm kənsˈɪdɚd ɐ tˈiːneɪdʒɚ.
+DUMMY2/p294/p294_094.wav|104|ɪt ʃˌʊd biː ɐ kəndˈɪʃən ʌv ɛmplˈɔɪmənt.
+DUMMY2/p269/p269_031.wav|94|ɪz ðɪs ˈækjʊɹət?
+DUMMY2/p275/p275_116.wav|40|ɪts nˌɑːt fˈɛɹ.
+DUMMY2/p265/p265_006.wav|73|wˌɛn ðə sˈʌnlaɪt stɹˈaɪks ɹˈeɪndɹɑːps ɪnðɪ ˈɛɹ, ðeɪ ˈækt æz ɐ pɹˈɪzəm ænd fˈɔːɹm ɐ ɹˈeɪnboʊ.
+DUMMY2/p285/p285_072.wav|2|mˈɪstɚɹ ˈɜːvaɪn sˈɛd mˈɪstɚ ɹˈæfɚɾi wʌz nˈaʊ ɪn ɡˈʊd spˈɪɹɪts.
+DUMMY2/p270/p270_167.wav|8|wiː dˈɪd wˌʌt wiː hædtə dˈuː.
+DUMMY2/p360/p360_397.wav|60|ɪt ɪz ɐ ɹɪlˈiːf.

inference.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import IPython.display as ipd\n",
+    "\n",
+    "import os\n",
+    "import json\n",
+    "import math\n",
+    "import torch\n",
+    "from torch import nn\n",
+    "from torch.nn import functional as F\n",
+    "from torch.utils.data import DataLoader\n",
+    "\n",
+    "import commons\n",
+    "import utils\n",
+    "from data_utils import TextAudioLoader, TextAudioCollate, TextAudioSpeakerLoader, TextAudioSpeakerCollate\n",
+    "from models import SynthesizerTrn\n",
+    "from text.symbols import symbols\n",
+    "from text import text_to_sequence\n",
+    "\n",
+    "from scipy.io.wavfile import write\n",
+    "\n",
+    "\n",
+    "def get_text(text, hps):\n",
+    "    text_norm = text_to_sequence(text, hps.data.text_cleaners)\n",
+    "    if hps.data.add_blank:\n",
+    "        text_norm = commons.intersperse(text_norm, 0)\n",
+    "    text_norm = torch.LongTensor(text_norm)\n",
+    "    return text_norm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## LJ Speech"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hps = utils.get_hparams_from_file(\"./configs/ljs_base.json\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "net_g = SynthesizerTrn(\n",
+    "    len(symbols),\n",
+    "    hps.data.filter_length // 2 + 1,\n",
+    "    hps.train.segment_size // hps.data.hop_length,\n",
+    "    **hps.model).cuda()\n",
+    "_ = net_g.eval()\n",
+    "\n",
+    "_ = utils.load_checkpoint(\"/path/to/pretrained_ljs.pth\", net_g, None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stn_tst = get_text(\"VITS is Awesome!\", hps)\n",
+    "with torch.no_grad():\n",
+    "    x_tst = stn_tst.cuda().unsqueeze(0)\n",
+    "    x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).cuda()\n",
+    "    audio = net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][0,0].data.cpu().float().numpy()\n",
+    "ipd.display(ipd.Audio(audio, rate=hps.data.sampling_rate, normalize=False))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## VCTK"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hps = utils.get_hparams_from_file(\"./configs/vctk_base.json\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "net_g = SynthesizerTrn(\n",
+    "    len(symbols),\n",
+    "    hps.data.filter_length // 2 + 1,\n",
+    "    hps.train.segment_size // hps.data.hop_length,\n",
+    "    n_speakers=hps.data.n_speakers,\n",
+    "    **hps.model).cuda()\n",
+    "_ = net_g.eval()\n",
+    "\n",
+    "_ = utils.load_checkpoint(\"/path/to/pretrained_vctk.pth\", net_g, None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stn_tst = get_text(\"VITS is Awesome!\", hps)\n",
+    "with torch.no_grad():\n",
+    "    x_tst = stn_tst.cuda().unsqueeze(0)\n",
+    "    x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).cuda()\n",
+    "    sid = torch.LongTensor([4]).cuda()\n",
+    "    audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][0,0].data.cpu().float().numpy()\n",
+    "ipd.display(ipd.Audio(audio, rate=hps.data.sampling_rate, normalize=False))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Voice Conversion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = TextAudioSpeakerLoader(hps.data.validation_files, hps.data)\n",
+    "collate_fn = TextAudioSpeakerCollate()\n",
+    "loader = DataLoader(dataset, num_workers=8, shuffle=False,\n",
+    "    batch_size=1, pin_memory=True,\n",
+    "    drop_last=True, collate_fn=collate_fn)\n",
+    "data_list = list(loader)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with torch.no_grad():\n",
+    "    x, x_lengths, spec, spec_lengths, y, y_lengths, sid_src = [x.cuda() for x in data_list[0]]\n",
+    "    sid_tgt1 = torch.LongTensor([1]).cuda()\n",
+    "    sid_tgt2 = torch.LongTensor([2]).cuda()\n",
+    "    sid_tgt3 = torch.LongTensor([4]).cuda()\n",
+    "    audio1 = net_g.voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt1)[0][0,0].data.cpu().float().numpy()\n",
+    "    audio2 = net_g.voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt2)[0][0,0].data.cpu().float().numpy()\n",
+    "    audio3 = net_g.voice_conversion(spec, spec_lengths, sid_src=sid_src, sid_tgt=sid_tgt3)[0][0,0].data.cpu().float().numpy()\n",
+    "print(\"Original SID: %d\" % sid_src.item())\n",
+    "ipd.display(ipd.Audio(y[0].cpu().numpy(), rate=hps.data.sampling_rate, normalize=False))\n",
+    "print(\"Converted SID: %d\" % sid_tgt1.item())\n",
+    "ipd.display(ipd.Audio(audio1, rate=hps.data.sampling_rate, normalize=False))\n",
+    "print(\"Converted SID: %d\" % sid_tgt2.item())\n",
+    "ipd.display(ipd.Audio(audio2, rate=hps.data.sampling_rate, normalize=False))\n",
+    "print(\"Converted SID: %d\" % sid_tgt3.item())\n",
+    "ipd.display(ipd.Audio(audio3, rate=hps.data.sampling_rate, normalize=False))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

kme.log

+nohup: ignoring input
+INFO:ljs_base:{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 20000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 64, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/ljs_audio_text_train_filelist.txt.cleaned', 'validation_files': 'filelists/ljs_audio_text_val_filelist.txt.cleaned', 'text_cleaners': ['english_cleaners2'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 0, 'cleaned_text': True}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [8, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False}, 'model_dir': './logs/ljs_base'}
+WARNING: Logging before InitGoogleLogging() is written to STDERR
+I0829 14:14:48.131174 68339 ProcessGroupNCCL.cpp:686] [Rank 1] ProcessGroupNCCL initialization options:NCCL_ASYNC_ERROR_HANDLING: 1, NCCL_DESYNC_DEBUG: 0, NCCL_ENABLE_TIMING: 0, NCCL_BLOCKING_WAIT: 0, TIMEOUT(ms): 1800000, USE_HIGH_PRIORITY_STREAM: 0, TORCH_DISTRIBUTED_DEBUG: OFF, NCCL_DEBUG: OFF, ID=94222121121904
+WARNING: Logging before InitGoogleLogging() is written to STDERR
+I0829 14:14:48.142663 68338 ProcessGroupNCCL.cpp:686] [Rank 0] ProcessGroupNCCL initialization options:NCCL_ASYNC_ERROR_HANDLING: 1, NCCL_DESYNC_DEBUG: 0, NCCL_ENABLE_TIMING: 0, NCCL_BLOCKING_WAIT: 0, TIMEOUT(ms): 1800000, USE_HIGH_PRIORITY_STREAM: 0, TORCH_DISTRIBUTED_DEBUG: OFF, NCCL_DEBUG: OFF, ID=94043438289712
+/usr/local/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
+  warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
+/usr/local/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
+  warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
+I0829 14:14:50.271715 68338 ProcessGroupNCCL.cpp:1340] NCCL_DEBUG: N/A
+SynthesizerTrn(
+  (enc_p): TextEncoder(
+    (emb): Embedding(178, 192)
+    (encoder): Encoder(
+      (drop): Dropout(p=0.1, inplace=False)
+      (attn_layers): ModuleList(
+        (0-5): 6 x MultiHeadAttention(
+          (conv_q): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          (conv_k): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          (conv_v): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          (conv_o): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          (drop): Dropout(p=0.1, inplace=False)
+        )
+      )
+      (norm_layers_1): ModuleList(
+        (0-5): 6 x LayerNorm()
+      )
+      (ffn_layers): ModuleList(
+        (0-5): 6 x FFN(
+          (conv_1): Conv1d(192, 768, kernel_size=(3,), stride=(1,))
+          (conv_2): Conv1d(768, 192, kernel_size=(3,), stride=(1,))
+          (drop): Dropout(p=0.1, inplace=False)
+        )
+      )
+      (norm_layers_2): ModuleList(
+        (0-5): 6 x LayerNorm()
+      )
+    )
+    (proj): Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+  )
+  (dec): Generator(
+    (conv_pre): Conv1d(192, 512, kernel_size=(7,), stride=(1,), padding=(3,))
+    (ups): ModuleList(
+      (0): ConvTranspose1d(512, 256, kernel_size=(16,), stride=(8,), padding=(4,))
+      (1): ConvTranspose1d(256, 128, kernel_size=(16,), stride=(8,), padding=(4,))
+      (2): ConvTranspose1d(128, 64, kernel_size=(4,), stride=(2,), padding=(1,))
+      (3): ConvTranspose1d(64, 32, kernel_size=(4,), stride=(2,), padding=(1,))
+    )
+    (resblocks): ModuleList(
+      (0): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(256, 256, kernel_size=(3,), stride=(1,), padding=(1,))
+          (1): Conv1d(256, 256, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,))
+          (2): Conv1d(256, 256, kernel_size=(3,), stride=(1,), padding=(5,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(256, 256, kernel_size=(3,), stride=(1,), padding=(1,))
+        )
+      )
+      (1): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(256, 256, kernel_size=(7,), stride=(1,), padding=(3,))
+          (1): Conv1d(256, 256, kernel_size=(7,), stride=(1,), padding=(9,), dilation=(3,))
+          (2): Conv1d(256, 256, kernel_size=(7,), stride=(1,), padding=(15,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(256, 256, kernel_size=(7,), stride=(1,), padding=(3,))
+        )
+      )
+      (2): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(256, 256, kernel_size=(11,), stride=(1,), padding=(5,))
+          (1): Conv1d(256, 256, kernel_size=(11,), stride=(1,), padding=(15,), dilation=(3,))
+          (2): Conv1d(256, 256, kernel_size=(11,), stride=(1,), padding=(25,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(256, 256, kernel_size=(11,), stride=(1,), padding=(5,))
+        )
+      )
+      (3): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=(1,))
+          (1): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,))
+          (2): Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=(5,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(128, 128, kernel_size=(3,), stride=(1,), padding=(1,))
+        )
+      )
+      (4): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(128, 128, kernel_size=(7,), stride=(1,), padding=(3,))
+          (1): Conv1d(128, 128, kernel_size=(7,), stride=(1,), padding=(9,), dilation=(3,))
+          (2): Conv1d(128, 128, kernel_size=(7,), stride=(1,), padding=(15,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(128, 128, kernel_size=(7,), stride=(1,), padding=(3,))
+        )
+      )
+      (5): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(128, 128, kernel_size=(11,), stride=(1,), padding=(5,))
+          (1): Conv1d(128, 128, kernel_size=(11,), stride=(1,), padding=(15,), dilation=(3,))
+          (2): Conv1d(128, 128, kernel_size=(11,), stride=(1,), padding=(25,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(128, 128, kernel_size=(11,), stride=(1,), padding=(5,))
+        )
+      )
+      (6): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(64, 64, kernel_size=(3,), stride=(1,), padding=(1,))
+          (1): Conv1d(64, 64, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,))
+          (2): Conv1d(64, 64, kernel_size=(3,), stride=(1,), padding=(5,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(64, 64, kernel_size=(3,), stride=(1,), padding=(1,))
+        )
+      )
+      (7): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(64, 64, kernel_size=(7,), stride=(1,), padding=(3,))
+          (1): Conv1d(64, 64, kernel_size=(7,), stride=(1,), padding=(9,), dilation=(3,))
+          (2): Conv1d(64, 64, kernel_size=(7,), stride=(1,), padding=(15,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(64, 64, kernel_size=(7,), stride=(1,), padding=(3,))
+        )
+      )
+      (8): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(64, 64, kernel_size=(11,), stride=(1,), padding=(5,))
+          (1): Conv1d(64, 64, kernel_size=(11,), stride=(1,), padding=(15,), dilation=(3,))
+          (2): Conv1d(64, 64, kernel_size=(11,), stride=(1,), padding=(25,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(64, 64, kernel_size=(11,), stride=(1,), padding=(5,))
+        )
+      )
+      (9): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(32, 32, kernel_size=(3,), stride=(1,), padding=(1,))
+          (1): Conv1d(32, 32, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,))
+          (2): Conv1d(32, 32, kernel_size=(3,), stride=(1,), padding=(5,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(32, 32, kernel_size=(3,), stride=(1,), padding=(1,))
+        )
+      )
+      (10): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(32, 32, kernel_size=(7,), stride=(1,), padding=(3,))
+          (1): Conv1d(32, 32, kernel_size=(7,), stride=(1,), padding=(9,), dilation=(3,))
+          (2): Conv1d(32, 32, kernel_size=(7,), stride=(1,), padding=(15,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(32, 32, kernel_size=(7,), stride=(1,), padding=(3,))
+        )
+      )
+      (11): ResBlock1(
+        (convs1): ModuleList(
+          (0): Conv1d(32, 32, kernel_size=(11,), stride=(1,), padding=(5,))
+          (1): Conv1d(32, 32, kernel_size=(11,), stride=(1,), padding=(15,), dilation=(3,))
+          (2): Conv1d(32, 32, kernel_size=(11,), stride=(1,), padding=(25,), dilation=(5,))
+        )
+        (convs2): ModuleList(
+          (0-2): 3 x Conv1d(32, 32, kernel_size=(11,), stride=(1,), padding=(5,))
+        )
+      )
+    )
+    (conv_post): Conv1d(32, 1, kernel_size=(7,), stride=(1,), padding=(3,), bias=False)
+  )
+  (enc_q): PosteriorEncoder(
+    (pre): Conv1d(513, 192, kernel_size=(1,), stride=(1,))
+    (enc): WN(
+      (in_layers): ModuleList(
+        (0-15): 16 x Conv1d(192, 384, kernel_size=(5,), stride=(1,), padding=(2,))
+      )
+      (res_skip_layers): ModuleList(
+        (0-14): 15 x Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+        (15): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+      )
+      (drop): Dropout(p=0, inplace=False)
+    )
+    (proj): Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+  )
+  (flow): ResidualCouplingBlock(
+    (flows): ModuleList(
+      (0): ResidualCouplingLayer(
+        (pre): Conv1d(96, 192, kernel_size=(1,), stride=(1,))
+        (enc): WN(
+          (in_layers): ModuleList(
+            (0-3): 4 x Conv1d(192, 384, kernel_size=(5,), stride=(1,), padding=(2,))
+          )
+          (res_skip_layers): ModuleList(
+            (0-2): 3 x Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+            (3): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (drop): Dropout(p=0, inplace=False)
+        )
+        (post): Conv1d(192, 96, kernel_size=(1,), stride=(1,))
+      )
+      (1): Flip()
+      (2): ResidualCouplingLayer(
+        (pre): Conv1d(96, 192, kernel_size=(1,), stride=(1,))
+        (enc): WN(
+          (in_layers): ModuleList(
+            (0-3): 4 x Conv1d(192, 384, kernel_size=(5,), stride=(1,), padding=(2,))
+          )
+          (res_skip_layers): ModuleList(
+            (0-2): 3 x Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+            (3): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (drop): Dropout(p=0, inplace=False)
+        )
+        (post): Conv1d(192, 96, kernel_size=(1,), stride=(1,))
+      )
+      (3): Flip()
+      (4): ResidualCouplingLayer(
+        (pre): Conv1d(96, 192, kernel_size=(1,), stride=(1,))
+        (enc): WN(
+          (in_layers): ModuleList(
+            (0-3): 4 x Conv1d(192, 384, kernel_size=(5,), stride=(1,), padding=(2,))
+          )
+          (res_skip_layers): ModuleList(
+            (0-2): 3 x Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+            (3): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (drop): Dropout(p=0, inplace=False)
+        )
+        (post): Conv1d(192, 96, kernel_size=(1,), stride=(1,))
+      )
+      (5): Flip()
+      (6): ResidualCouplingLayer(
+        (pre): Conv1d(96, 192, kernel_size=(1,), stride=(1,))
+        (enc): WN(
+          (in_layers): ModuleList(
+            (0-3): 4 x Conv1d(192, 384, kernel_size=(5,), stride=(1,), padding=(2,))
+          )
+          (res_skip_layers): ModuleList(
+            (0-2): 3 x Conv1d(192, 384, kernel_size=(1,), stride=(1,))
+            (3): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (drop): Dropout(p=0, inplace=False)
+        )
+        (post): Conv1d(192, 96, kernel_size=(1,), stride=(1,))
+      )
+      (7): Flip()
+    )
+  )
+  (dp): StochasticDurationPredictor(
+    (log_flow): Log()
+    (flows): ModuleList(
+      (0): ElementwiseAffine()
+      (1): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (2): Flip()
+      (3): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (4): Flip()
+      (5): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (6): Flip()
+      (7): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (8): Flip()
+    )
+    (post_pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+    (post_proj): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+    (post_convs): DDSConv(
+      (drop): Dropout(p=0.5, inplace=False)
+      (convs_sep): ModuleList(
+        (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+        (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+        (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+      )
+      (convs_1x1): ModuleList(
+        (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+      )
+      (norms_1): ModuleList(
+        (0-2): 3 x LayerNorm()
+      )
+      (norms_2): ModuleList(
+        (0-2): 3 x LayerNorm()
+      )
+    )
+    (post_flows): ModuleList(
+      (0): ElementwiseAffine()
+      (1): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (2): Flip()
+      (3): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (4): Flip()
+      (5): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (6): Flip()
+      (7): ConvFlow(
+        (pre): Conv1d(1, 192, kernel_size=(1,), stride=(1,))
+        (convs): DDSConv(
+          (drop): Dropout(p=0.0, inplace=False)
+          (convs_sep): ModuleList(
+            (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+            (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+            (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+          )
+          (convs_1x1): ModuleList(
+            (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+          )
+          (norms_1): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+          (norms_2): ModuleList(
+            (0-2): 3 x LayerNorm()
+          )
+        )
+        (proj): Conv1d(192, 29, kernel_size=(1,), stride=(1,))
+      )
+      (8): Flip()
+    )
+    (pre): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+    (proj): Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+    (convs): DDSConv(
+      (drop): Dropout(p=0.5, inplace=False)
+      (convs_sep): ModuleList(
+        (0): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(1,), groups=192)
+        (1): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(3,), dilation=(3,), groups=192)
+        (2): Conv1d(192, 192, kernel_size=(3,), stride=(1,), padding=(9,), dilation=(9,), groups=192)
+      )
+      (convs_1x1): ModuleList(
+        (0-2): 3 x Conv1d(192, 192, kernel_size=(1,), stride=(1,))
+      )
+      (norms_1): ModuleList(
+        (0-2): 3 x LayerNorm()
+      )
+      (norms_2): ModuleList(
+        (0-2): 3 x LayerNorm()
+      )
+    )
+  )
+)
+MultiPeriodDiscriminator(
+  (discriminators): ModuleList(
+    (0): DiscriminatorS(
+      (convs): ModuleList(
+        (0): Conv1d(1, 16, kernel_size=(15,), stride=(1,), padding=(7,))
+        (1): Conv1d(16, 64, kernel_size=(41,), stride=(4,), padding=(20,), groups=4)
+        (2): Conv1d(64, 256, kernel_size=(41,), stride=(4,), padding=(20,), groups=16)
+        (3): Conv1d(256, 1024, kernel_size=(41,), stride=(4,), padding=(20,), groups=64)
+        (4): Conv1d(1024, 1024, kernel_size=(41,), stride=(4,), padding=(20,), groups=256)
+        (5): Conv1d(1024, 1024, kernel_size=(5,), stride=(1,), padding=(2,))
+      )
+      (conv_post): Conv1d(1024, 1, kernel_size=(3,), stride=(1,), padding=(1,))
+    )
+    (1-5): 5 x DiscriminatorP(
+      (convs): ModuleList(
+        (0): Conv2d(1, 32, kernel_size=(5, 1), stride=(3, 1), padding=(2, 0))
+        (1): Conv2d(32, 128, kernel_size=(5, 1), stride=(3, 1), padding=(2, 0))
+        (2): Conv2d(128, 512, kernel_size=(5, 1), stride=(3, 1), padding=(2, 0))
+        (3): Conv2d(512, 1024, kernel_size=(5, 1), stride=(3, 1), padding=(2, 0))
+        (4): Conv2d(1024, 1024, kernel_size=(5, 1), stride=(1, 1), padding=(2, 0))
+      )
+      (conv_post): Conv2d(1024, 1, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0))
+    )
+  )
+)
+./logs/ljs_base/G_0.pth
+INFO:ljs_base:Loaded checkpoint './logs/ljs_base/G_0.pth' (iteration 1)
+./logs/ljs_base/G_0.pth
+INFO:root:Loaded checkpoint './logs/ljs_base/G_0.pth' (iteration 1)
+./logs/ljs_base/D_0.pth
+INFO:ljs_base:Loaded checkpoint './logs/ljs_base/D_0.pth' (iteration 1)
+INFO:ljs_base:====> Epoch: 1 | Total Samples: 12492
+./logs/ljs_base/D_0.pth
+INFO:root:Loaded checkpoint './logs/ljs_base/D_0.pth' (iteration 1)
+/usr/local/lib/python3.10/site-packages/torch/autograd/__init__.py:251: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [1, 9, 96], strides() = [46944, 96, 1]
+bucket_view.sizes() = [1, 9, 96], strides() = [864, 96, 1] (Triggered internally at /data/jenkins_workspace/workspace/pytorch@4/torch/csrc/distributed/c10d/reducer.cpp:320.)
+  Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+/usr/local/lib/python3.10/site-packages/torch/autograd/__init__.py:251: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
+grad.sizes() = [1, 9, 96], strides() = [48096, 96, 1]
+bucket_view.sizes() = [1, 9, 96], strides() = [864, 96, 1] (Triggered internally at /data/jenkins_workspace/workspace/pytorch@4/torch/csrc/distributed/c10d/reducer.cpp:320.)
+  Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+INFO:ljs_base:Train Epoch: 1 [0%]
+INFO:ljs_base:[4.670844554901123, 2.8319339752197266, 0.3068731725215912, 73.78945922851562, 1.4018142223358154, 91.56964874267578, 0, 0.0002]
+DEBUG:matplotlib:matplotlib data path: /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data
+DEBUG:matplotlib:CONFIGDIR=/root/.config/matplotlib
+DEBUG:matplotlib:interactive is False
+DEBUG:matplotlib:platform is linux
+INFO:ljs_base:Saving model and optimizer state at iteration 1 to ./logs/ljs_base/G_0.pth
+INFO:ljs_base:Saving model and optimizer state at iteration 1 to ./logs/ljs_base/D_0.pth
+INFO:ljs_base:====> Epoch: 1
+INFO:ljs_base:====> FPS: 25.03245151912063
+INFO:ljs_base:====> Epoch: 2 | Total Samples: 12492
+run.sh: line 13: 68143 Killed                  python train.py -c configs/ljs_base.json -m ljs_base

losses.py

+import torch 
+from torch.nn import functional as F
+
+import commons
+
+
+def feature_loss(fmap_r, fmap_g):
+  loss = 0
+  for dr, dg in zip(fmap_r, fmap_g):
+    for rl, gl in zip(dr, dg):
+      rl = rl.float().detach()
+      gl = gl.float()
+      loss += torch.mean(torch.abs(rl - gl))
+
+  return loss * 2 
+
+
+def discriminator_loss(disc_real_outputs, disc_generated_outputs):
+  loss = 0
+  r_losses = []
+  g_losses = []
+  for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
+    dr = dr.float()
+    dg = dg.float()
+    r_loss = torch.mean((1-dr)**2)
+    g_loss = torch.mean(dg**2)
+    loss += (r_loss + g_loss)
+    r_losses.append(r_loss.item())
+    g_losses.append(g_loss.item())
+
+  return loss, r_losses, g_losses
+
+
+def generator_loss(disc_outputs):
+  loss = 0
+  gen_losses = []
+  for dg in disc_outputs:
+    dg = dg.float()
+    l = torch.mean((1-dg)**2)
+    gen_losses.append(l)
+    loss += l
+
+  return loss, gen_losses
+
+
+def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):
+  """
+  z_p, logs_q: [b, h, t_t]
+  m_p, logs_p: [b, h, t_t]
+  """
+  z_p = z_p.float()
+  logs_q = logs_q.float()
+  m_p = m_p.float()
+  logs_p = logs_p.float()
+  z_mask = z_mask.float()
+
+  kl = logs_p - logs_q - 0.5
+  kl += 0.5 * ((z_p - m_p)**2) * torch.exp(-2. * logs_p)
+  kl = torch.sum(kl * z_mask)
+  l = kl / torch.sum(z_mask)
+  return l

mel_processing.py

+import math
+import os
+import random
+import torch
+from torch import nn
+import torch.nn.functional as F
+import torch.utils.data
+import numpy as np
+import librosa
+import librosa.util as librosa_util
+from librosa.util import normalize, pad_center, tiny
+from scipy.signal import get_window
+from scipy.io.wavfile import read
+from librosa.filters import mel as librosa_mel_fn
+MAX_WAV_VALUE = 32768.0
+
+def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
+    """
+    PARAMS
+    ------
+    C: compression factor
+    """
+    return torch.log(torch.clamp(x, min=clip_val) * C)
+
+
+def dynamic_range_decompression_torch(x, C=1):
+    """
+    PARAMS
+    ------
+    C: compression factor used to compress
+    """
+    return torch.exp(x) / C
+
+
+def spectral_normalize_torch(magnitudes):
+    output = dynamic_range_compression_torch(magnitudes)
+    return output
+
+
+def spectral_de_normalize_torch(magnitudes):
+    output = dynamic_range_decompression_torch(magnitudes)
+    return output
+
+
+mel_basis = {}
+hann_window = {}
+
+
+def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+
+    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+                      center=center, pad_mode='reflect', normalized=False, onesided=True)
+    spec = torch.view_as_real(spec)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+    return spec
+
+
+def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
+    global mel_basis
+    dtype_device = str(spec.dtype) + '_' + str(spec.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=spec.dtype, device=spec.device)
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+    return spec
+
+
+def mel_spectrogram_torch(y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax, center=False):
+    if torch.min(y) < -1.:
+        print('min value is ', torch.min(y))
+    if torch.max(y) > 1.:
+        print('max value is ', torch.max(y))
+
+    global mel_basis, hann_window
+    dtype_device = str(y.dtype) + '_' + str(y.device)
+    fmax_dtype_device = str(fmax) + '_' + dtype_device
+    wnsize_dtype_device = str(win_size) + '_' + dtype_device
+    if fmax_dtype_device not in mel_basis:
+        mel = librosa_mel_fn(sr=sampling_rate, n_fft=n_fft, n_mels=num_mels, fmin=fmin, fmax=fmax)
+        mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
+    if wnsize_dtype_device not in hann_window:
+        hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
+
+    y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
+    y = y.squeeze(1)
+
+    spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
+                      center=center, pad_mode='reflect', normalized=False, onesided=True)
+    spec = torch.view_as_real(spec)
+
+    spec = torch.sqrt(spec.pow(2).sum(-1) + 1e-6)
+
+    spec = torch.matmul(mel_basis[fmax_dtype_device], spec)
+    spec = spectral_normalize_torch(spec)
+
+    return spec

models.py

+import copy
+import math
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+import commons
+import modules
+import attentions
+import monotonic_align
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from commons import init_weights, get_padding
+
+
+class StochasticDurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, n_flows=4, gin_channels=0):
+    super().__init__()
+    filter_channels = in_channels # it needs to be removed from future version.
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.log_flow = modules.Log()
+    self.flows = nn.ModuleList()
+    self.flows.append(modules.ElementwiseAffine(2))
+    for i in range(n_flows):
+      self.flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.flows.append(modules.Flip())
+
+    self.post_pre = nn.Conv1d(1, filter_channels, 1)
+    self.post_proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.post_convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    self.post_flows = nn.ModuleList()
+    self.post_flows.append(modules.ElementwiseAffine(2))
+    for i in range(4):
+      self.post_flows.append(modules.ConvFlow(2, filter_channels, kernel_size, n_layers=3))
+      self.post_flows.append(modules.Flip())
+
+    self.pre = nn.Conv1d(in_channels, filter_channels, 1)
+    self.proj = nn.Conv1d(filter_channels, filter_channels, 1)
+    self.convs = modules.DDSConv(filter_channels, kernel_size, n_layers=3, p_dropout=p_dropout)
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, filter_channels, 1)
+
+  def forward(self, x, x_mask, w=None, g=None, reverse=False, noise_scale=1.0):
+    x = torch.detach(x)
+    x = self.pre(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.convs(x, x_mask)
+    x = self.proj(x) * x_mask
+
+    if not reverse:
+      flows = self.flows
+      assert w is not None
+
+      logdet_tot_q = 0 
+      h_w = self.post_pre(w)
+      h_w = self.post_convs(h_w, x_mask)
+      h_w = self.post_proj(h_w) * x_mask
+      e_q = torch.randn(w.size(0), 2, w.size(2)).to(device=x.device, dtype=x.dtype) * x_mask
+      z_q = e_q
+      for flow in self.post_flows:
+        z_q, logdet_q = flow(z_q, x_mask, g=(x + h_w))
+        logdet_tot_q += logdet_q
+      z_u, z1 = torch.split(z_q, [1, 1], 1) 
+      u = torch.sigmoid(z_u) * x_mask
+      z0 = (w - u) * x_mask
+      logdet_tot_q += torch.sum((F.logsigmoid(z_u) + F.logsigmoid(-z_u)) * x_mask, [1,2])
+      logq = torch.sum(-0.5 * (math.log(2*math.pi) + (e_q**2)) * x_mask, [1,2]) - logdet_tot_q
+
+      logdet_tot = 0
+      z0, logdet = self.log_flow(z0, x_mask)
+      logdet_tot += logdet
+      z = torch.cat([z0, z1], 1)
+      for flow in flows:
+        z, logdet = flow(z, x_mask, g=x, reverse=reverse)
+        logdet_tot = logdet_tot + logdet
+      nll = torch.sum(0.5 * (math.log(2*math.pi) + (z**2)) * x_mask, [1,2]) - logdet_tot
+      return nll + logq # [b]
+    else:
+      flows = list(reversed(self.flows))
+      ###DEBUG
+      flows = flows[:-2] + [flows[-1]] # remove a useless vflow
+      ###DEBUG
+      z = torch.randn(x.size(0), 2, x.size(2)).to(device=x.device, dtype=x.dtype) * noise_scale
+      for flow in flows:
+        z = flow(z, x_mask, g=x, reverse=reverse)
+      z0, z1 = torch.split(z, [1, 1], 1)
+      logw = z0
+      return logw
+
+
+class DurationPredictor(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, p_dropout, gin_channels=0):
+    super().__init__()
+
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.gin_channels = gin_channels
+
+    self.drop = nn.Dropout(p_dropout)
+    self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_1 = modules.LayerNorm(filter_channels)
+    self.conv_2 = nn.Conv1d(filter_channels, filter_channels, kernel_size, padding=kernel_size//2)
+    self.norm_2 = modules.LayerNorm(filter_channels)
+    self.proj = nn.Conv1d(filter_channels, 1, 1)
+
+    if gin_channels != 0:
+      self.cond = nn.Conv1d(gin_channels, in_channels, 1)
+
+  def forward(self, x, x_mask, g=None):
+    x = torch.detach(x)
+    if g is not None:
+      g = torch.detach(g)
+      x = x + self.cond(g)
+    x = self.conv_1(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_1(x)
+    x = self.drop(x)
+    x = self.conv_2(x * x_mask)
+    x = torch.relu(x)
+    x = self.norm_2(x)
+    x = self.drop(x)
+    x = self.proj(x * x_mask)
+    return x * x_mask
+
+
+class TextEncoder(nn.Module):
+  def __init__(self,
+      n_vocab,
+      out_channels,
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout):
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+
+    self.emb = nn.Embedding(n_vocab, hidden_channels)
+    nn.init.normal_(self.emb.weight, 0.0, hidden_channels**-0.5)
+
+    self.encoder = attentions.Encoder(
+      hidden_channels,
+      filter_channels,
+      n_heads,
+      n_layers,
+      kernel_size,
+      p_dropout)
+    self.proj= nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths):
+    x = self.emb(x) * math.sqrt(self.hidden_channels) # [b, t, h]
+    ##DEBUG
+    x = torch.transpose(x, 1, -1).contiguous() # [b, h, t]
+    ##DEBUG
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+
+    x = self.encoder(x * x_mask, x_mask)
+    stats = self.proj(x) * x_mask
+
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    return x, m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      n_flows=4,
+      gin_channels=0):
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.n_flows = n_flows
+    self.gin_channels = gin_channels
+
+    self.flows = nn.ModuleList()
+    for i in range(n_flows):
+      self.flows.append(modules.ResidualCouplingLayer(channels, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels, mean_only=True))
+      self.flows.append(modules.Flip())
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    if not reverse:
+      for flow in self.flows:
+        x, _ = flow(x, x_mask, g=g, reverse=reverse)
+    else:
+      for flow in reversed(self.flows):
+        x = flow(x, x_mask, g=g, reverse=reverse)
+    return x
+
+
+class PosteriorEncoder(nn.Module):
+  def __init__(self,
+      in_channels,
+      out_channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      gin_channels=0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.out_channels = out_channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+
+    self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+    self.enc = modules.WN(hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=gin_channels)
+    self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+  def forward(self, x, x_lengths, g=None):
+    x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(x.dtype)
+    x = self.pre(x) * x_mask
+    x = self.enc(x, x_mask, g=g)
+    stats = self.proj(x) * x_mask
+    m, logs = torch.split(stats, self.out_channels, dim=1)
+    z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+    return z, m, logs, x_mask
+
+
+class Generator(torch.nn.Module):
+    def __init__(self, initial_channel, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=0):
+        super(Generator, self).__init__()
+        self.num_kernels = len(resblock_kernel_sizes)
+        self.num_upsamples = len(upsample_rates)
+        self.conv_pre = Conv1d(initial_channel, upsample_initial_channel, 7, 1, padding=3)
+        resblock = modules.ResBlock1 if resblock == '1' else modules.ResBlock2
+
+        self.ups = nn.ModuleList()
+        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+            self.ups.append(weight_norm(
+                ConvTranspose1d(upsample_initial_channel//(2**i), upsample_initial_channel//(2**(i+1)),
+                                k, u, padding=(k-u)//2)))
+
+        self.resblocks = nn.ModuleList()
+        for i in range(len(self.ups)):
+            ch = upsample_initial_channel//(2**(i+1))
+            for j, (k, d) in enumerate(zip(resblock_kernel_sizes, resblock_dilation_sizes)):
+                self.resblocks.append(resblock(ch, k, d))
+
+        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+        self.ups.apply(init_weights)
+
+        if gin_channels != 0:
+            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+    def forward(self, x, g=None):
+        x = self.conv_pre(x)
+        if g is not None:
+          x = x + self.cond(g)
+
+        for i in range(self.num_upsamples):
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            x = self.ups[i](x)
+            xs = None
+            for j in range(self.num_kernels):
+                if xs is None:
+                    xs = self.resblocks[i*self.num_kernels+j](x)
+                else:
+                    xs += self.resblocks[i*self.num_kernels+j](x)
+            x = xs / self.num_kernels
+        x = F.leaky_relu(x)
+        x = self.conv_post(x)
+        x = torch.tanh(x)
+
+        return x
+
+    def remove_weight_norm(self):
+        print('Removing weight norm...')
+        for l in self.ups:
+            remove_weight_norm(l)
+        for l in self.resblocks:
+            l.remove_weight_norm()
+
+
+class DiscriminatorP(torch.nn.Module):
+    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+        super(DiscriminatorP, self).__init__()
+        self.period = period
+        self.use_spectral_norm = use_spectral_norm
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv2d(1, 32, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(32, 128, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(128, 512, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(512, 1024, (kernel_size, 1), (stride, 1), padding=(get_padding(kernel_size, 1), 0))),
+            norm_f(Conv2d(1024, 1024, (kernel_size, 1), 1, padding=(get_padding(kernel_size, 1), 0))),
+        ])
+        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+    def forward(self, x):
+        fmap = []
+
+        # 1d to 2d
+        b, c, t = x.shape
+        if t % self.period != 0: # pad first
+            n_pad = self.period - (t % self.period)
+            x = F.pad(x, (0, n_pad), "reflect")
+            t = t + n_pad
+        ###DEBUG
+        x = x.view(b, c, t // self.period, self.period).contiguous()
+        ###DEBUG
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class DiscriminatorS(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(DiscriminatorS, self).__init__()
+        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+        self.convs = nn.ModuleList([
+            norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+            norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+            norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+            norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+            norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+            norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+        ])
+        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+    def forward(self, x):
+        fmap = []
+
+        for l in self.convs:
+            x = l(x)
+            x = F.leaky_relu(x, modules.LRELU_SLOPE)
+            fmap.append(x)
+        x = self.conv_post(x)
+        fmap.append(x)
+        x = torch.flatten(x, 1, -1)
+
+        return x, fmap
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+    def __init__(self, use_spectral_norm=False):
+        super(MultiPeriodDiscriminator, self).__init__()
+        periods = [2,3,5,7,11]
+
+        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+        discs = discs + [DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods]
+        self.discriminators = nn.ModuleList(discs)
+
+    def forward(self, y, y_hat):
+        y_d_rs = []
+        y_d_gs = []
+        fmap_rs = []
+        fmap_gs = []
+        for i, d in enumerate(self.discriminators):
+            y_d_r, fmap_r = d(y)
+            y_d_g, fmap_g = d(y_hat)
+            y_d_rs.append(y_d_r)
+            y_d_gs.append(y_d_g)
+            fmap_rs.append(fmap_r)
+            fmap_gs.append(fmap_g)
+
+        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+
+class SynthesizerTrn(nn.Module):
+  """
+  Synthesizer for Training
+  """
+
+  def __init__(self, 
+    n_vocab,
+    spec_channels,
+    segment_size,
+    inter_channels,
+    hidden_channels,
+    filter_channels,
+    n_heads,
+    n_layers,
+    kernel_size,
+    p_dropout,
+    resblock, 
+    resblock_kernel_sizes, 
+    resblock_dilation_sizes, 
+    upsample_rates, 
+    upsample_initial_channel, 
+    upsample_kernel_sizes,
+    n_speakers=0,
+    gin_channels=0,
+    use_sdp=True,
+    **kwargs):
+
+    super().__init__()
+    self.n_vocab = n_vocab
+    self.spec_channels = spec_channels
+    self.inter_channels = inter_channels
+    self.hidden_channels = hidden_channels
+    self.filter_channels = filter_channels
+    self.n_heads = n_heads
+    self.n_layers = n_layers
+    self.kernel_size = kernel_size
+    self.p_dropout = p_dropout
+    self.resblock = resblock
+    self.resblock_kernel_sizes = resblock_kernel_sizes
+    self.resblock_dilation_sizes = resblock_dilation_sizes
+    self.upsample_rates = upsample_rates
+    self.upsample_initial_channel = upsample_initial_channel
+    self.upsample_kernel_sizes = upsample_kernel_sizes
+    self.segment_size = segment_size
+    self.n_speakers = n_speakers
+    self.gin_channels = gin_channels
+
+    self.use_sdp = use_sdp
+
+    self.enc_p = TextEncoder(n_vocab,
+        inter_channels,
+        hidden_channels,
+        filter_channels,
+        n_heads,
+        n_layers,
+        kernel_size,
+        p_dropout)
+    self.dec = Generator(inter_channels, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, gin_channels=gin_channels)
+    self.enc_q = PosteriorEncoder(spec_channels, inter_channels, hidden_channels, 5, 1, 16, gin_channels=gin_channels)
+    self.flow = ResidualCouplingBlock(inter_channels, hidden_channels, 5, 1, 4, gin_channels=gin_channels)
+
+    if use_sdp:
+      self.dp = StochasticDurationPredictor(hidden_channels, 192, 3, 0.5, 4, gin_channels=gin_channels)
+    else:
+      self.dp = DurationPredictor(hidden_channels, 256, 3, 0.5, gin_channels=gin_channels)
+
+    if n_speakers > 1:
+      self.emb_g = nn.Embedding(n_speakers, gin_channels)
+
+  def forward(self, x, x_lengths, y, y_lengths, sid=None):
+
+    x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
+    if self.n_speakers > 0:
+      g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
+    else:
+      g = None
+
+    z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+    z_p = self.flow(z, y_mask, g=g)
+
+    with torch.no_grad():
+      # negative cross-entropy
+      s_p_sq_r = torch.exp(-2 * logs_p) # [b, d, t]
+      neg_cent1 = torch.sum(-0.5 * math.log(2 * math.pi) - logs_p, [1], keepdim=True) # [b, 1, t_s]
+      ###DEBUG
+      neg_cent2 = torch.matmul(-0.5 * (z_p ** 2).transpose(1, 2).contiguous(), s_p_sq_r) # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
+      neg_cent3 = torch.matmul(z_p.transpose(1, 2).contiguous(), (m_p * s_p_sq_r)) # [b, t_t, d] x [b, d, t_s] = [b, t_t, t_s]
+      ###
+      neg_cent4 = torch.sum(-0.5 * (m_p ** 2) * s_p_sq_r, [1], keepdim=True) # [b, 1, t_s]
+      neg_cent = neg_cent1 + neg_cent2 + neg_cent3 + neg_cent4
+
+      attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
+      attn = monotonic_align.maximum_path(neg_cent, attn_mask.squeeze(1)).unsqueeze(1).detach()
+
+    w = attn.sum(2)
+    if self.use_sdp:
+      l_length = self.dp(x, x_mask, w, g=g)
+      l_length = l_length / torch.sum(x_mask)
+    else:
+      logw_ = torch.log(w + 1e-6) * x_mask
+      logw = self.dp(x, x_mask, g=g)
+      l_length = torch.sum((logw - logw_)**2, [1,2]) / torch.sum(x_mask) # for averaging 
+
+    # expand prior
+    ###DEBUG
+    m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2).contiguous()).transpose(1, 2).contiguous()
+    logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2).contiguous()).transpose(1, 2).contiguous()
+    ###
+
+    z_slice, ids_slice = commons.rand_slice_segments(z, y_lengths, self.segment_size)
+    o = self.dec(z_slice, g=g)
+    return o, l_length, attn, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+  def infer(self, x, x_lengths, sid=None, noise_scale=1, length_scale=1, noise_scale_w=1., max_len=None):
+    x, m_p, logs_p, x_mask = self.enc_p(x, x_lengths)
+    if self.n_speakers > 0:
+      g = self.emb_g(sid).unsqueeze(-1) # [b, h, 1]
+    else:
+      g = None
+
+    if self.use_sdp:
+      logw = self.dp(x, x_mask, g=g, reverse=True, noise_scale=noise_scale_w)
+    else:
+      logw = self.dp(x, x_mask, g=g)
+    w = torch.exp(logw) * x_mask * length_scale
+    w_ceil = torch.ceil(w)
+    y_lengths = torch.clamp_min(torch.sum(w_ceil, [1, 2]), 1).long()
+    y_mask = torch.unsqueeze(commons.sequence_mask(y_lengths, None), 1).to(x_mask.dtype)
+    attn_mask = torch.unsqueeze(x_mask, 2) * torch.unsqueeze(y_mask, -1)
+    attn = commons.generate_path(w_ceil, attn_mask)
+    ###DEBUG
+    m_p = torch.matmul(attn.squeeze(1), m_p.transpose(1, 2).contiguous()).transpose(1, 2).contiguous() # [b, t', t], [b, t, d] -> [b, d, t']
+    logs_p = torch.matmul(attn.squeeze(1), logs_p.transpose(1, 2).contiguous()).transpose(1, 2).contiguous() # [b, t', t], [b, t, d] -> [b, d, t']
+    ###DEBUG
+    z_p = m_p + torch.randn_like(m_p) * torch.exp(logs_p) * noise_scale
+    z = self.flow(z_p, y_mask, g=g, reverse=True)
+    o = self.dec((z * y_mask)[:,:,:max_len], g=g)
+    return o, attn, y_mask, (z, z_p, m_p, logs_p)
+
+  def voice_conversion(self, y, y_lengths, sid_src, sid_tgt):
+    assert self.n_speakers > 0, "n_speakers have to be larger than 0."
+    g_src = self.emb_g(sid_src).unsqueeze(-1)
+    g_tgt = self.emb_g(sid_tgt).unsqueeze(-1)
+    z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g_src)
+    z_p = self.flow(z, y_mask, g=g_src)
+    z_hat = self.flow(z_p, y_mask, g=g_tgt, reverse=True)
+    o_hat = self.dec(z_hat * y_mask, g=g_tgt)
+    return o_hat, y_mask, (z, z_p, z_hat)
+

modules.py

+import copy
+import math
+import numpy as np
+import scipy
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+import commons
+from commons import init_weights, get_padding
+from transforms import piecewise_rational_quadratic_transform
+
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+  def __init__(self, channels, eps=1e-5):
+    super().__init__()
+    self.channels = channels
+    self.eps = eps
+
+    self.gamma = nn.Parameter(torch.ones(channels))
+    self.beta = nn.Parameter(torch.zeros(channels))
+
+  def forward(self, x):
+    ###DEBUG
+    x = x.transpose(1, -1).contiguous()
+    x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+    return x.transpose(1, -1).contiguous()
+    ###DEBUG
+ 
+class ConvReluNorm(nn.Module):
+  def __init__(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout):
+    super().__init__()
+    self.in_channels = in_channels
+    self.hidden_channels = hidden_channels
+    self.out_channels = out_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+    assert n_layers > 1, "Number of layers should be larger than 0."
+
+    self.conv_layers = nn.ModuleList()
+    self.norm_layers = nn.ModuleList()
+    self.conv_layers.append(nn.Conv1d(in_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+    self.norm_layers.append(LayerNorm(hidden_channels))
+    self.relu_drop = nn.Sequential(
+        nn.ReLU(),
+        nn.Dropout(p_dropout))
+    for _ in range(n_layers-1):
+      self.conv_layers.append(nn.Conv1d(hidden_channels, hidden_channels, kernel_size, padding=kernel_size//2))
+      self.norm_layers.append(LayerNorm(hidden_channels))
+    self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask):
+    x_org = x
+    for i in range(self.n_layers):
+      x = self.conv_layers[i](x * x_mask)
+      x = self.norm_layers[i](x)
+      x = self.relu_drop(x)
+    x = x_org + self.proj(x)
+    return x * x_mask
+
+
+class DDSConv(nn.Module):
+  """
+  Dialted and Depth-Separable Convolution
+  """
+  def __init__(self, channels, kernel_size, n_layers, p_dropout=0.):
+    super().__init__()
+    self.channels = channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.p_dropout = p_dropout
+
+    self.drop = nn.Dropout(p_dropout)
+    self.convs_sep = nn.ModuleList()
+    self.convs_1x1 = nn.ModuleList()
+    self.norms_1 = nn.ModuleList()
+    self.norms_2 = nn.ModuleList()
+    for i in range(n_layers):
+      dilation = kernel_size ** i
+      padding = (kernel_size * dilation - dilation) // 2
+      self.convs_sep.append(nn.Conv1d(channels, channels, kernel_size, 
+          groups=channels, dilation=dilation, padding=padding
+      ))
+      self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+      self.norms_1.append(LayerNorm(channels))
+      self.norms_2.append(LayerNorm(channels))
+
+  def forward(self, x, x_mask, g=None):
+    if g is not None:
+      x = x + g
+    for i in range(self.n_layers):
+      y = self.convs_sep[i](x * x_mask)
+      y = self.norms_1[i](y)
+      y = F.gelu(y)
+      y = self.convs_1x1[i](y)
+      y = self.norms_2[i](y)
+      y = F.gelu(y)
+      y = self.drop(y)
+      x = x + y
+    return x * x_mask
+
+
+class WN(torch.nn.Module):
+  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=0, p_dropout=0):
+    super(WN, self).__init__()
+    assert(kernel_size % 2 == 1)
+    self.hidden_channels =hidden_channels
+    self.kernel_size = kernel_size,
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.gin_channels = gin_channels
+    self.p_dropout = p_dropout
+
+    self.in_layers = torch.nn.ModuleList()
+    self.res_skip_layers = torch.nn.ModuleList()
+    self.drop = nn.Dropout(p_dropout)
+
+    if gin_channels != 0:
+      cond_layer = torch.nn.Conv1d(gin_channels, 2*hidden_channels*n_layers, 1)
+      self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name='weight')
+
+    for i in range(n_layers):
+      dilation = dilation_rate ** i
+      padding = int((kernel_size * dilation - dilation) / 2)
+      in_layer = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
+                                 dilation=dilation, padding=padding)
+      in_layer = torch.nn.utils.weight_norm(in_layer, name='weight')
+      self.in_layers.append(in_layer)
+
+      # last one is not necessary
+      if i < n_layers - 1:
+        res_skip_channels = 2 * hidden_channels
+      else:
+        res_skip_channels = hidden_channels
+
+      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+      res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
+      self.res_skip_layers.append(res_skip_layer)
+
+  def forward(self, x, x_mask, g=None, **kwargs):
+    output = torch.zeros_like(x)
+    n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+    if g is not None:
+      g = self.cond_layer(g)
+
+    for i in range(self.n_layers):
+      x_in = self.in_layers[i](x)
+      if g is not None:
+        cond_offset = i * 2 * self.hidden_channels
+        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
+      else:
+        g_l = torch.zeros_like(x_in)
+
+      acts = commons.fused_add_tanh_sigmoid_multiply(
+          x_in,
+          g_l,
+          n_channels_tensor)
+      acts = self.drop(acts)
+
+      res_skip_acts = self.res_skip_layers[i](acts)
+      if i < self.n_layers - 1:
+        res_acts = res_skip_acts[:,:self.hidden_channels,:]
+        x = (x + res_acts) * x_mask
+        output = output + res_skip_acts[:,self.hidden_channels:,:]
+      else:
+        output = output + res_skip_acts
+    return output * x_mask
+
+  def remove_weight_norm(self):
+    if self.gin_channels != 0:
+      torch.nn.utils.remove_weight_norm(self.cond_layer)
+    for l in self.in_layers:
+      torch.nn.utils.remove_weight_norm(l)
+    for l in self.res_skip_layers:
+     torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+        super(ResBlock1, self).__init__()
+        self.convs1 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[2],
+                               padding=get_padding(kernel_size, dilation[2])))
+        ])
+        self.convs1.apply(init_weights)
+
+        self.convs2 = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
+                               padding=get_padding(kernel_size, 1)))
+        ])
+        self.convs2.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c1, c2 in zip(self.convs1, self.convs2):
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c1(xt)
+            xt = F.leaky_relu(xt, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c2(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs1:
+            remove_weight_norm(l)
+        for l in self.convs2:
+            remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+        super(ResBlock2, self).__init__()
+        self.convs = nn.ModuleList([
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
+                               padding=get_padding(kernel_size, dilation[0]))),
+            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
+                               padding=get_padding(kernel_size, dilation[1])))
+        ])
+        self.convs.apply(init_weights)
+
+    def forward(self, x, x_mask=None):
+        for c in self.convs:
+            xt = F.leaky_relu(x, LRELU_SLOPE)
+            if x_mask is not None:
+                xt = xt * x_mask
+            xt = c(xt)
+            x = xt + x
+        if x_mask is not None:
+            x = x * x_mask
+        return x
+
+    def remove_weight_norm(self):
+        for l in self.convs:
+            remove_weight_norm(l)
+
+
+class Log(nn.Module):
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+      logdet = torch.sum(-y, [1, 2])
+      return y, logdet
+    else:
+      x = torch.exp(x) * x_mask
+      return x
+    
+
+class Flip(nn.Module):
+  def forward(self, x, *args, reverse=False, **kwargs):
+    x = torch.flip(x, [1])
+    if not reverse:
+      logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+      return x, logdet
+    else:
+      return x
+
+
+class ElementwiseAffine(nn.Module):
+  def __init__(self, channels):
+    super().__init__()
+    self.channels = channels
+    self.m = nn.Parameter(torch.zeros(channels,1))
+    self.logs = nn.Parameter(torch.zeros(channels,1))
+
+  def forward(self, x, x_mask, reverse=False, **kwargs):
+    if not reverse:
+      y = self.m + torch.exp(self.logs) * x
+      y = y * x_mask
+      logdet = torch.sum(self.logs * x_mask, [1,2])
+      return y, logdet
+    else:
+      x = (x - self.m) * torch.exp(-self.logs) * x_mask
+      return x
+
+
+class ResidualCouplingLayer(nn.Module):
+  def __init__(self,
+      channels,
+      hidden_channels,
+      kernel_size,
+      dilation_rate,
+      n_layers,
+      p_dropout=0,
+      gin_channels=0,
+      mean_only=False):
+    assert channels % 2 == 0, "channels should be divisible by 2"
+    super().__init__()
+    self.channels = channels
+    self.hidden_channels = hidden_channels
+    self.kernel_size = kernel_size
+    self.dilation_rate = dilation_rate
+    self.n_layers = n_layers
+    self.half_channels = channels // 2
+    self.mean_only = mean_only
+
+    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+    self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers, p_dropout=p_dropout, gin_channels=gin_channels)
+    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+    self.post.weight.data.zero_()
+    self.post.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0) * x_mask
+    h = self.enc(h, x_mask, g=g)
+    stats = self.post(h) * x_mask
+    if not self.mean_only:
+      m, logs = torch.split(stats, [self.half_channels]*2, 1)
+    else:
+      m = stats
+      logs = torch.zeros_like(m)
+
+    if not reverse:
+      x1 = m + x1 * torch.exp(logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      logdet = torch.sum(logs, [1,2])
+      return x, logdet
+    else:
+      x1 = (x1 - m) * torch.exp(-logs) * x_mask
+      x = torch.cat([x0, x1], 1)
+      return x
+
+
+class ConvFlow(nn.Module):
+  def __init__(self, in_channels, filter_channels, kernel_size, n_layers, num_bins=10, tail_bound=5.0):
+    super().__init__()
+    self.in_channels = in_channels
+    self.filter_channels = filter_channels
+    self.kernel_size = kernel_size
+    self.n_layers = n_layers
+    self.num_bins = num_bins
+    self.tail_bound = tail_bound
+    self.half_channels = in_channels // 2
+
+    self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+    self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.)
+    self.proj = nn.Conv1d(filter_channels, self.half_channels * (num_bins * 3 - 1), 1)
+    self.proj.weight.data.zero_()
+    self.proj.bias.data.zero_()
+
+  def forward(self, x, x_mask, g=None, reverse=False):
+    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
+    h = self.pre(x0)
+    h = self.convs(h, x_mask, g=g)
+    h = self.proj(h) * x_mask
+
+    b, c, t = x0.shape
+    ###DEBUG
+    h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2).contiguous() # [b, cx?, t] -> [b, c, t, ?]
+    ###
+    unnormalized_widths = h[..., :self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_heights = h[..., self.num_bins:2*self.num_bins] / math.sqrt(self.filter_channels)
+    unnormalized_derivatives = h[..., 2 * self.num_bins:]
+
+    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
+        unnormalized_widths,
+        unnormalized_heights,
+        unnormalized_derivatives,
+        inverse=reverse,
+        tails='linear',
+        tail_bound=self.tail_bound
+    )
+
+    x = torch.cat([x0, x1], 1) * x_mask
+    logdet = torch.sum(logabsdet * x_mask, [1,2])
+    if not reverse:
+        return x, logdet
+    else:
+        return x

monotonic_align/__init__.py

+import numpy as np
+import torch
+from .monotonic_align.core import maximum_path_c
+
+
+def maximum_path(neg_cent, mask):
+  """ Cython optimized version.
+  neg_cent: [b, t_t, t_s]
+  mask: [b, t_t, t_s]
+  """
+  device = neg_cent.device
+  dtype = neg_cent.dtype
+  neg_cent = neg_cent.data.cpu().numpy().astype(np.float32)
+  path = np.zeros(neg_cent.shape, dtype=np.int32)
+
+  t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(np.int32)
+  t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(np.int32)
+  maximum_path_c(path, neg_cent, t_t_max, t_s_max)
+  return torch.from_numpy(path).to(device=device, dtype=dtype)