- 12 May, 2022 1 commit
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John Reese authored
Summary: Applies the black-fbsource codemod with the new build of pyfmt. paintitblack Reviewed By: lisroach Differential Revision: D36324783 fbshipit-source-id: 280c09e88257e5e569ab729691165d8dedd767bc
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- 28 Apr, 2022 1 commit
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moto authored
Summary: libmad integration should be enabled only from source-build Pull Request resolved: https://github.com/pytorch/audio/pull/2354 Reviewed By: nateanl Differential Revision: D36012035 Pulled By: mthrok fbshipit-source-id: adeda8cbfd418f96245909cae6862b648a6915a7
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- 26 Apr, 2022 1 commit
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Caroline Chen authored
Summary: Add support for lexicon free decoding based on [fairseq's](https://github.com/pytorch/fairseq/blob/main/examples/speech_recognition/new/decoders/flashlight_decoder.py#L53) implementation. Reached numerical parity with fairseq's decoder in offline experimentation Follow ups - Add pretrained LM support for lex free decoding - Add example in tutorial - Replace flashlight C++ source code with flashlight text submodule - [optional] fairseq compatibility test Pull Request resolved: https://github.com/pytorch/audio/pull/2342 Reviewed By: nateanl Differential Revision: D35856104 Pulled By: carolineechen fbshipit-source-id: b64286550984df906ebb747e82f6fb1f21948ac7
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- 21 Apr, 2022 1 commit
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hwangjeff authored
Summary: PyTorch Lite, which is becoming a standard for mobile PyTorch usage, does not support containers containing custom classes. Consequently, because TorchAudio's RNN-T decoder currently returns and accepts lists of `Hypothesis` namedtuples, it is not compatible with PyTorch Lite. This PR resolves said incompatibility by changing the underlying implementation of `Hypothesis` to tuple. Pull Request resolved: https://github.com/pytorch/audio/pull/2339 Reviewed By: nateanl Differential Revision: D35806529 Pulled By: hwangjeff fbshipit-source-id: 9cbae5504722390511d35e7f9966af2519ccede5
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- 13 Apr, 2022 1 commit
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hwangjeff authored
Summary: Tutorial notebooks that leverage TorchAudio prototype features don't run as-is on Google Colab due to its runtime's not having nightly builds pre-installed. To make it easier for users to run said notebooks in Colab, this PR adds a code block that installs nightly Pytorch and TorchAudio builds as a comment that users can copy and run locally. Pull Request resolved: https://github.com/pytorch/audio/pull/2325 Reviewed By: xiaohui-zhang Differential Revision: D35597753 Pulled By: hwangjeff fbshipit-source-id: 59914e492ad72e31c0136a48cd88d697e8ea5f6c
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- 25 Mar, 2022 1 commit
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Caroline Chen authored
Summary: add function to download pretrained files for LibriSpeech 3-gram/4-gram KenLM, tests, and updated tutorial Pull Request resolved: https://github.com/pytorch/audio/pull/2275 Reviewed By: mthrok Differential Revision: D35115418 Pulled By: carolineechen fbshipit-source-id: 83ff22380fce9c753bb4a7b7e3d89aa66c2831c0
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- 24 Mar, 2022 2 commits
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Caroline Chen authored
Summary: rendered: - [tutorial](https://output.circle-artifacts.com/output/job/e7fb5a23-87cf-4dd5-b4a8-8b4f91e20eb4/artifacts/0/docs/tutorials/asr_inference_with_ctc_decoder_tutorial.html) - [docs](https://output.circle-artifacts.com/output/job/e7fb5a23-87cf-4dd5-b4a8-8b4f91e20eb4/artifacts/0/docs/prototype.ctc_decoder.html) Pull Request resolved: https://github.com/pytorch/audio/pull/2278 Reviewed By: mthrok Differential Revision: D35097734 Pulled By: carolineechen fbshipit-source-id: 1e5d5fff0b7740757cca358cf3ea44c6488fcd5c
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2288 Reviewed By: hwangjeff Differential Revision: D35099492 Pulled By: mthrok fbshipit-source-id: 955c5e617469009ae2600d2764d601d794ee916f
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- 22 Mar, 2022 1 commit
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Hagen Wierstorf authored
Summary: The calculation of the SNR in tha data augmentation examples seems to be wrong to me:  If we start from the definition of the signal-to-noise ratio using the root mean square value we get: ``` SNR = 20 log10 ( rms(scale * speech) / rms(noise) ) ``` this can be transformed to ``` scale = 10^(SNR/20) rms(noise) / rms(speech) ``` In the example not `rms` is used but `lambda x: x.norm(p=2)`, but as we have the same length of the speech and noise signal, we have ``` rms(noise) / rms(speech) = noise.norm(p=2) / speech.norm(p=2) ``` this would lead us to: ``` 10^(SNR/20) = e^(SNR / 10) ``` which is not true. Hence I changed `e^(SNR / 10)` to `10^(SNR/20)`. For the proposed SNR values of 20 dB, 10 dB, 3 dB the value of the scale would change from 7.39, 2.72, 1.35 to 10.0, 3.16, 1.41. Pull Request resolved: https://github.com/pytorch/audio/pull/2285 Reviewed By: nateanl Differential Revision: D35047737 Pulled By: mthrok fbshipit-source-id: ac24c8fd48ef06b4b611e35163084644330a3ef3
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- 17 Mar, 2022 1 commit
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2281 Reviewed By: carolineechen Differential Revision: D34939494 Pulled By: mthrok fbshipit-source-id: e97100b95a8e3d3e28805d8fab43b66120c2254d
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- 10 Mar, 2022 1 commit
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moto authored
Summary: Follo-up on post-commit review from https://github.com/pytorch/audio/issues/2202 Pull Request resolved: https://github.com/pytorch/audio/pull/2270 Reviewed By: hwangjeff Differential Revision: D34793460 Pulled By: mthrok fbshipit-source-id: 039ddeca015fc77b89c571820b7ef2b0857f5723
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- 26 Feb, 2022 1 commit
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moto authored
Summary: This commit adds tutorial for device ASR, and update API for device streaming. The changes for the interface are 1. Add `timeout` and `backoff` parameters to `process_packet` and `stream` methods. 2. Move `fill_buffer` method to private. When dealing with device stream, there are situations where the device buffer is not ready and the system returns `EAGAIN`. In such case, the previous implementation of `process_packet` method raised an exception in Python layer , but for device ASR, this is inefficient. A better approach is to retry within C++ layer in blocking manner. The new `timeout` parameter serves this purpose. Pull Request resolved: https://github.com/pytorch/audio/pull/2202 Reviewed By: nateanl Differential Revision: D34475829 Pulled By: mthrok fbshipit-source-id: bb6d0b125d800f87d189db40815af06fbd4cab59
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- 17 Feb, 2022 1 commit
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moto authored
Summary: https://554729-90321822-gh.circle-artifacts.com/0/docs/tutorials/online_asr_tutorial.html 1. Add figure to explain the caching 2. Fix the initialization of stream iterator Pull Request resolved: https://github.com/pytorch/audio/pull/2226 Reviewed By: carolineechen Differential Revision: D34265971 Pulled By: mthrok fbshipit-source-id: 243301e74c4040f4b8cd111b363e70da60e5dae4
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- 15 Feb, 2022 1 commit
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moto authored
Summary: Updating the context cacher so that fetched audio chunk is used for inference immediately. https://github.com/pytorch/audio/pull/2202#discussion_r802838174 Pull Request resolved: https://github.com/pytorch/audio/pull/2213 Reviewed By: hwangjeff Differential Revision: D34235230 Pulled By: mthrok fbshipit-source-id: 6e4aee7cca34ca81e40c0cb13497182f20f7f04e
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- 09 Feb, 2022 1 commit
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hwangjeff authored
Summary: Yesterday's release of librosa 0.9.0 made args keyword-only and changed default padding from "reflect" to "zero" for some functions. This PR adjusts callsites in our tutorials and tests accordingly. Pull Request resolved: https://github.com/pytorch/audio/pull/2208 Reviewed By: mthrok Differential Revision: D34099793 Pulled By: hwangjeff fbshipit-source-id: 4e2642cdda8aae6d0a928befaf1bbb3873d229bc
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- 03 Feb, 2022 1 commit
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moto authored
Summary: * tutorial for streaming API https://541810-90321822-gh.circle-artifacts.com/0/docs/tutorials/streaming_api_tutorial.html * tutorial for online speech recognition with Emformer RNN-T https://541810-90321822-gh.circle-artifacts.com/0/docs/tutorials/online_asr_tutorial.html Pull Request resolved: https://github.com/pytorch/audio/pull/2193 Reviewed By: hwangjeff Differential Revision: D33971312 Pulled By: mthrok fbshipit-source-id: f9b69114255f15eaf4463ca85b3efb0ba321a95f
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- 02 Feb, 2022 1 commit
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Caroline Chen authored
Summary: resulting tutorial: https://538358-90321822-gh.circle-artifacts.com/0/docs/tutorials/asr_inference_with_ctc_decoder_tutorial.html - add visualization for timestep alignments - modify section organization for decoder construction Pull Request resolved: https://github.com/pytorch/audio/pull/2188 Reviewed By: mthrok Differential Revision: D33954937 Pulled By: carolineechen fbshipit-source-id: 8f397229d74c994b8793a30623e1de4c19ebd401
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- 31 Jan, 2022 1 commit
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moto authored
Summary: Changing the URL of tutorial assets to `download.pytorch.org` which is more appropriate for user facing materials. Pull Request resolved: https://github.com/pytorch/audio/pull/2182 Reviewed By: nateanl Differential Revision: D33887839 Pulled By: mthrok fbshipit-source-id: 30569672e8caf30aae5476036dfdadc8ebd436bf
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- 27 Jan, 2022 1 commit
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Caroline Chen authored
Summary: Add support for CTC lexicon decoder without LM support by adding a non language model `ZeroLM` that returns score 0 for everything. Generalize the decoder class/API a bit to support this, adding it as an option for the kenlm decoder at the moment (will likely be separated out from kenlm when adding support for other kinds of LMs in the future) Pull Request resolved: https://github.com/pytorch/audio/pull/2174 Reviewed By: hwangjeff, nateanl Differential Revision: D33798674 Pulled By: carolineechen fbshipit-source-id: ef8265f1d046011b143597b3b7c691566b08dcde
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- 26 Jan, 2022 1 commit
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Caroline Chen authored
Summary: following up on https://github.com/pytorch/audio/pull/2141#discussion_r779055465, adding brief beam search description and linking to resources Pull Request resolved: https://github.com/pytorch/audio/pull/2173 Reviewed By: nateanl Differential Revision: D33791731 Pulled By: carolineechen fbshipit-source-id: 603fdd177c9a3c8276a4692fb7bb385bd01b9bfb
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- 20 Jan, 2022 1 commit
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yonMaor authored
Summary: Closes https://github.com/pytorch/audio/issues/2162 Pull Request resolved: https://github.com/pytorch/audio/pull/2163 Reviewed By: nateanl Differential Revision: D33666354 Pulled By: mthrok fbshipit-source-id: 3e7a963b9ac85046317df8d5dab91af363e5668b
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- 07 Jan, 2022 1 commit
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Caroline Chen authored
Summary: Add explanation and demonstration of different beam search decoder parameters. Additionally use a better sample audio file and load in with token list instead of tokens file. Pull Request resolved: https://github.com/pytorch/audio/pull/2141 Reviewed By: mthrok Differential Revision: D33463230 Pulled By: carolineechen fbshipit-source-id: d3dd6452b03d4fc2e095d778189c66f7161e4c68
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- 29 Dec, 2021 1 commit
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moto authored
Summary: ### Change list * Split the documentation of prototypes * Add a new API reference section dedicated for prototypes. * Hide the signature of KenLMLexiconDecoder constructor. (cc carolineechen ) * https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.ctc_decoder.html#torchaudio.prototype.ctc_decoder.KenLMLexiconDecoder * Hide the signature of RNNT constructor. (cc hwangjeff ) * https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.rnnt.html#torchaudio.prototype.RNNT * Tweak CTC tutorial * Replace hyperlinks to API reference with backlinks * Add `progress=False` to download ### Follow-up RNNT decoder and CTC decode returns their own `Hypothesis` classes. When I tried to add Hypothesis of CTC decode to the documentation, the build process complains that it's ambiguous. I think the Hypothesis classes can be put inside of each decoder. (if TorchScript supports it) or make the name different, but in that case the interface of each Hypothesis has to be generic enough. ### Before https://pytorch.org/audio/main/prototype.html <img width="1390" alt="Screen Shot 2021-12-28 at 1 05 53 PM" src="https://user-images.githubusercontent.com/855818/147594425-6c7f8126-ab76-4edc-a616-a00901e7e9ef.png"> ### After https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.html <img width="1202" alt="Screen Shot 2021-12-28 at 8 37 35 PM" src="https://user-images.githubusercontent.com/855818/147619281-8152b1ae-e127-40b2-a944-dc11b114b629.png"> https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.rnnt.html <img width="1415" alt="Screen Shot 2021-12-28 at 8 38 27 PM" src="https://user-images.githubusercontent.com/855818/147619331-077b55b5-c5e9-47ab-bfe6-873e41c738c8.png"> https://489516-90321822-gh.circle-artifacts.com/0/docs/prototype.ctc_decoder.html <img width="1417" alt="Screen Shot 2021-12-28 at 8 39 04 PM" src="https://user-images.githubusercontent.com/855818/147619364-63df3457-a4b2-4223-973f-f4301bd45280.png"> Pull Request resolved: https://github.com/pytorch/audio/pull/2108 Reviewed By: hwangjeff, carolineechen, nateanl Differential Revision: D33340816 Pulled By: mthrok fbshipit-source-id: 870edfadbe41d6f8abaf78fdb7017b3980dfe187
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- 28 Dec, 2021 2 commits
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Caroline Chen authored
Summary: demonstrate usage of the CTC beam search decoder w/ lexicon constraint and KenLM support, on a LibriSpeech sample and using a pretrained wav2vec2 model rendered: https://485200-90321822-gh.circle-artifacts.com/0/docs/tutorials/asr_inference_with_ctc_decoder_tutorial.html follow-ups: - incorporate `nbest` - demonstrate customizability of different beam search parameters Pull Request resolved: https://github.com/pytorch/audio/pull/2106 Reviewed By: mthrok Differential Revision: D33340946 Pulled By: carolineechen fbshipit-source-id: 0ab838375d96a035d54ed5b5bd9ab4dc8d19adb7
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moto authored
Summary: This commit updates the documentation configuration so that if an API (function or class) is used in tutorials, then it automatically add the links to the tutorials. It also adds `py:func:` so that it's easy to jump from tutorials to API reference. Note: the use of `py:func:` is not required to be recognized by Shpinx-gallery. * https://482162-90321822-gh.circle-artifacts.com/0/docs/transforms.html#feature-extractions <img width="776" alt="Screen Shot 2021-12-24 at 12 41 43 PM" src="https://user-images.githubusercontent.com/855818/147367407-cd86f114-7177-426a-b5ee-a25af17ae476.png"> * https://482162-90321822-gh.circle-artifacts.com/0/docs/transforms.html#mvdr <img width="769" alt="Screen Shot 2021-12-24 at 12 42 31 PM" src="https://user-images.githubusercontent.com/855818/147367422-01fd245f-2f25-4875-a206-910e17ae0161.png"> Pull Request resolved: https://github.com/pytorch/audio/pull/2101 Reviewed By: hwangjeff Differential Revision: D33311283 Pulled By: mthrok fbshipit-source-id: e0c124d2a761e0f8d81c3d14c4ffc836ffffe288
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- 23 Dec, 2021 1 commit
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Joao Gomes authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/2096 run: `arc lint --apply-patches --paths-cmd 'hg files -I "./**/*.py"'` Reviewed By: mthrok Differential Revision: D33297351 fbshipit-source-id: 7bf5956edf0717c5ca90219f72414ff4eeaf5aa8
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- 21 Dec, 2021 1 commit
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moto authored
Summary: 1. Reorder Audio display so that audios are playable from browser in doc 2. Add link to function documentations https://470342-90321822-gh.circle-artifacts.com/0/docs/tutorials/audio_data_augmentation_tutorial.html Pull Request resolved: https://github.com/pytorch/audio/pull/2082 Reviewed By: carolineechen Differential Revision: D33227725 Pulled By: mthrok fbshipit-source-id: c7ee360b6f9b84c8e0a9b72193b98487d03b57ab
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- 11 Nov, 2021 1 commit
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nateanl authored
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- 10 Nov, 2021 1 commit
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Krishna Kalyan authored
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- 05 Nov, 2021 4 commits
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moto authored
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moto authored
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moto authored
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moto authored
* Refactor tutorial organization * Merge tutorial subdirectoris under to examples/gallery/tutorials * Do not use index.rst generated by Sphinx-gallery * Instead use flat structure so that all the tutorials are listed in left menu * Use `_assets` dir for artifacts of tutorials
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