- 24 Jul, 2023 1 commit
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Pingchuan Ma authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3489 Reviewed By: mthrok Differential Revision: D47726448 Pulled By: mpc001 fbshipit-source-id: 3d5aa7646c6bb816dcbbf70c61e98404bb148841
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- 18 Jul, 2023 1 commit
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moto authored
Summary: Now that GPU video decoders are available in doc CI, we run the tutorials with GPU decoders. Pull Request resolved: https://github.com/pytorch/audio/pull/3478 Differential Revision: D47519672 Pulled By: mthrok fbshipit-source-id: 2f95243100e9c75e17c2b4d306da164f0e31f8f2
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- 15 Jul, 2023 1 commit
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moto authored
Summary: The nightly builds support FFmpeg version 4, 5 and 6. Pull Request resolved: https://github.com/pytorch/audio/pull/3480 Differential Revision: D47482841 Pulled By: mthrok fbshipit-source-id: 88267f5e83ddc7b1e866b35e57a87b985e2c78c9
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- 05 Jul, 2023 1 commit
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Zhaoheng Ni authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3433 Current design of forced_align accept 2D Tensor for `log_probs` and 1D Tensor for `targets`. To make the API simple, the PR make changes to only support batch Tensors (3D Tensor for `log_probs` and 2D Tensor for `targets`). Reviewed By: mthrok Differential Revision: D46657526 fbshipit-source-id: af17ec3f92f1a2c46dba91c6db2488a11de36f89
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- 28 Jun, 2023 1 commit
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3449 Differential Revision: D47094402 Pulled By: mthrok fbshipit-source-id: 43e6994604f0e6c06a5f19c5e8599e2ce12ae622
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- 26 Jun, 2023 1 commit
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3442 Differential Revision: D46797481 Pulled By: mthrok fbshipit-source-id: 3513037cbb8f2edb70fdab0fec5c7c554a697abe
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- 21 Jun, 2023 1 commit
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Xiaohui Zhang authored
Summary: Splitting the multilingual example part into another tutorial. Pull Request resolved: https://github.com/pytorch/audio/pull/3443 Reviewed By: mthrok Differential Revision: D46802844 Pulled By: xiaohui-zhang fbshipit-source-id: a7093053cac8b79d650d4f665db7fde2d8254998
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- 16 Jun, 2023 1 commit
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Pingchuan Ma authored
Summary: This PR adds a data preparation recipe that uses the ultra face detector to extract full-face video. The resulting video output is then used as input for training and evaluating RNNT-based models for automatic speech recognition (ASR), visual speech recognition (VSR), and audio-visual ASR (AV-ASR) on the LRS3 dataset. This PR also updates the word error rate (WER) for AV-ASR LRS3 models and improves the code readability. Pull Request resolved: https://github.com/pytorch/audio/pull/3421 Reviewed By: mpc001 Differential Revision: D46799748 Pulled By: mthrok fbshipit-source-id: 97af3feac0592b240617faaffa4c0ac8cef614a9
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- 15 Jun, 2023 1 commit
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moto authored
Summary: * Fix backtrack visualization (the cooridnate was off-by-one.) * Add note about the simplification and the new align API * Explicitly handle SOS and EOS Pull Request resolved: https://github.com/pytorch/audio/pull/3440 Reviewed By: xiaohui-zhang Differential Revision: D46761282 Pulled By: mthrok fbshipit-source-id: b0b6c9754674e8e23543e9f002e29b55102c92f8
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- 07 Jun, 2023 1 commit
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3415 Differential Revision: D46526437 Pulled By: mthrok fbshipit-source-id: f78d19c19d7e68f67712412de35d9ed50f47263b
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- 06 Jun, 2023 1 commit
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moto authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3410 Differential Revision: D46496786 Pulled By: mthrok fbshipit-source-id: e517b273c40b340f39ce7db7ab1be1c3eb5f2059
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- 04 Jun, 2023 1 commit
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Zhaoheng Ni authored
Summary: There are some BC-Breaking changes from pytorch_lightning to lightning library. The PR adjust those changes to support latest lightning library. Pull Request resolved: https://github.com/pytorch/audio/pull/3396 Reviewed By: mthrok Differential Revision: D46345206 Pulled By: nateanl fbshipit-source-id: 59469c15dc5fe5466a99a5b5380eb4f98c2c633f
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- 02 Jun, 2023 2 commits
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moto authored
Summary: This commit removes compute_kaldi_pitch function and the underlying Kaldi integration from torchaudio. Kaldi pitch function was added in a short period of time by integrating the original Kaldi implementation, instead of reimplementing it in PyTorch. The Kaldi integration employed a hack which replaces the base vector/matrix implementation of Kaldi with PyTorch Tensor so that there is only one blas library within torchaudio. Recently, we are making torchaudio more lean, and we don't see a wide adoption of kaldi_pitch feature, so we decided to remove them. See some of the discussion https://github.com/pytorch/audio/issues/1269 Pull Request resolved: https://github.com/pytorch/audio/pull/3368 Differential Revision: D46406176 Pulled By: mthrok fbshipit-source-id: ee5e24d825188f379979ddccd680c7323b119b1e
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moto authored
Summary: Replace sox_effects with `torchaudio.io.AudioEffector` 1. To show case the new and better feature 2. To prepare for the upcoming removal of file-like support object Pull Request resolved: https://github.com/pytorch/audio/pull/3375 Reviewed By: nateanl Differential Revision: D46379016 Pulled By: mthrok fbshipit-source-id: 70f24b62494204949f327f6ac6c49f315c9ee315
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- 31 May, 2023 1 commit
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Jeff Hwang authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3379 Fixes `RNNTBeamSearch.infer`'s docstring and removes unused import from tutorial. Reviewed By: mthrok Differential Revision: D46227174 fbshipit-source-id: 7c1c3f05a6476cb0437622dea6f3ae6cb3ea9468
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- 26 May, 2023 2 commits
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atalman authored
Summary: This reverts commit d38a7854. This is temporary revert to unblock unit test migration from circleci to github Pull Request resolved: https://github.com/pytorch/audio/pull/3377 Reviewed By: mthrok Differential Revision: D46230498 Pulled By: atalman fbshipit-source-id: 000d8a9ca00750fc1ca61f4c2cdd6e930a5ce46d
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Lakshmi Krishnan authored
Summary: This commit fixes the following issues affecting streaming decoding quality 1. The `init_b` hypothesis is only regenerated from blank token if no initial hypotheses are provided. 2. Allows the decoder to receive top-K hypothesis to continue decoding from, instead of using just the top hypothesis at each decoding step. This dramatically affects decoding quality especially for speech with long pauses and disfluencies. 3. Some minor errors regarding shape checking for length. This also means that the resulting output is the entire transcript up until that time step, instead of just the incremental change in transcript. Pull Request resolved: https://github.com/pytorch/audio/pull/3295 Reviewed By: nateanl Differential Revision: D46216113 Pulled By: hwangjeff fbshipit-source-id: 8f7efae28dcca4a052f434ca55a2795c9e5ec0b0
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- 25 May, 2023 1 commit
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Pingchuan Ma authored
Summary: This PR adds AV-ASR recipe which contains sample implementations of training and evaluation pipelines for RNNT based automatic, visual, and audio-visual (ASR, VSR, AV-ASR) models on LRS3. This repository includes both streaming/non-streaming modes. CC stavros99 xiaohui-zhang YumengTao mthrok nateanl hwangjeff Pull Request resolved: https://github.com/pytorch/audio/pull/3278 Reviewed By: nateanl Differential Revision: D46121550 Pulled By: mpc001 fbshipit-source-id: bb44b97ae25e87df2a73a707008be46af4ad0fc6
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- 23 May, 2023 1 commit
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Xiaohui Zhang authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3356 move the forced aligner tutorial to torchaudio, with some formatting changes Reviewed By: mthrok Differential Revision: D46060238 fbshipit-source-id: d90e7db5669a58d1e9ef5c2ec3c6d175b4e394ec
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- 21 May, 2023 2 commits
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Moto Hira authored
Differential Revision: D45960556 Original commit changeset: 93f2271f7130 Original Phabricator Diff: D45960556 fbshipit-source-id: d22883fbcf9c5f2bb5d49274bcc194bdffaca72a
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Xiaohui Zhang authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3351 move the forced aligner tutorial to torchaudio, with some formatting changes Reviewed By: vineelpratap, nateanl Differential Revision: D45960556 fbshipit-source-id: 93f2271f71307404e6a7732385cf7d646dc8ceaa
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- 16 May, 2023 1 commit
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moto authored
Summary: This commit upgrade the version of FFmpeg compiled against TorchAudio binary distribution to 5.0.4. FFmpeg 5.0 was released in Jan 2022, and many package managers provide a version of FFmpeg v5. Conda-forge lists 5.1 for all the platforms TorchAudio supports.https://anaconda.org/conda-forge/ffmpeg Pull Request resolved: https://github.com/pytorch/audio/pull/3298 Reviewed By: hwangjeff Differential Revision: D45865599 Pulled By: mthrok fbshipit-source-id: d95638eb80daaf477a710a992f4ead9b9009bb9b
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- 10 May, 2023 2 commits
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moto authored
Summary: https://output.circle-artifacts.com/output/job/fbfa6d9a-5014-42ac-8e77-c1e9565747e8/artifacts/0/docs/tutorials/effector_tutorial.html Pull Request resolved: https://github.com/pytorch/audio/pull/3226 Reviewed By: nateanl Differential Revision: D45402724 Pulled By: mthrok fbshipit-source-id: bc9d1bc071f6f5062b9cc35d743b4a3016306262
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moto authored
Summary: This commit is preparation for landing dispatcher switch in https://github.com/pytorch/audio/issues/3241 Making FFmpeg backend default causes some issues on tutorials, so this commit disable it. The IO tutorial will be updated after https://github.com/pytorch/audio/issues/3241 is landed to accommodate the change. Since it is necessary to mention the changes related to migration in the IO tutorial, I also update the IO documentation to include migration work so that it's easy to redirect. Pull Request resolved: https://github.com/pytorch/audio/pull/3285 Reviewed By: nateanl Differential Revision: D45671237 Pulled By: mthrok fbshipit-source-id: cb541f6bd93cd9920019b8ec83210ea69d34f133
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- 05 May, 2023 1 commit
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Zhaoheng Ni authored
Summary: Add scatter plots for STOI, PESQ, Si-SDR, and MOS scores to demonstrate the performance of `SquimObjective` and `SquimSubjective` models and how close they are to the ground truths. Pull Request resolved: https://github.com/pytorch/audio/pull/3313 Reviewed By: hwangjeff Differential Revision: D45620311 Pulled By: nateanl fbshipit-source-id: cb58ffd3744df4749b9385876da8de0cffd93557
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- 29 Apr, 2023 1 commit
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Zhaoheng Ni authored
Summary: The PR adds a tutorial that demonstrates how to use pre-trained `TorchAudio-SQUIM` pipelines to estimate objective and subjective metric scores (PESQ, STOI, Si-SDR, MOS). Pull Request resolved: https://github.com/pytorch/audio/pull/3279 Reviewed By: hwangjeff Differential Revision: D45415404 Pulled By: nateanl fbshipit-source-id: abcaeadcca0eabc2dca53b607eac6257a701c903
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- 28 Apr, 2023 1 commit
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Yuekai Zhang authored
Summary: This PR implements a CUDA based ctc prefix beam search decoder. Attach serveral benchmark results using V100 below: |decoder type| model |datasets | decoding time (secs)| beam size | batch size | model unit | subsampling times | vocab size | |--------------|---------|------|-----------------|------------|-------------|------------|-----------------------|------------| | cuctc | conformer nemo |dev clean |7.68s | 8 | 32 | bpe | 4 | 1000| | cuctc | conformer nemo |dev clean (sort by length) |1.6s | 8 | 32 | bpe | 4 | 1000| | cuctc | wav2vec2.0 torchaudio |dev clean |22s | 10 | 1 | char | 2 | 29| | cuctc | conformer espnet |aishell1 test | 5s | 10 | 24 | char | 4 | 4233| Note: 1. The design is to parallel computation through batch and vocab axis, for loop the frames axis. So it's more friendly with smaller sequence lengths, larger vocab size comparing with CPU implementations. 2. WER is the same as CPU implementations. However, it can't decode with LM now. Resolves: https://github.com/pytorch/audio/issues/2957. Pull Request resolved: https://github.com/pytorch/audio/pull/3096 Reviewed By: nateanl Differential Revision: D44709397 Pulled By: mthrok fbshipit-source-id: 3078c54a2b44dc00eb4a81b4c657487eeff8c155
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- 18 Apr, 2023 1 commit
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nateanl authored
Summary: The PR adds the training recipe of DNN beamforming for multi-channel speech enhancement. Pull Request resolved: https://github.com/pytorch/audio/pull/3036 Reviewed By: hwangjeff Differential Revision: D45061841 Pulled By: nateanl fbshipit-source-id: 48ede5dd579efe200669dbc83e9cb4dea809e4b4
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- 31 Mar, 2023 1 commit
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Nouran Ali authored
Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3222 Reviewed By: nateanl Differential Revision: D44539424 Pulled By: mthrok fbshipit-source-id: 8fbcb5f9918c9930c939bcd448493fa5cf604545
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- 29 Mar, 2023 1 commit
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moto authored
Summary: There is a part of StreamWriter tutorial that warns about corrupted AAC audio output, but this is no longer relevant thus this commit deletes it. Pull Request resolved: https://github.com/pytorch/audio/pull/3214 Reviewed By: nateanl Differential Revision: D44504030 Pulled By: mthrok fbshipit-source-id: 4d26d582e9fb87d4e6fa674c05fe3192bc223eef
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- 28 Mar, 2023 1 commit
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nateanl authored
Summary: Fix https://github.com/pytorch/audio/issues/3211 Pull Request resolved: https://github.com/pytorch/audio/pull/3212 Reviewed By: mthrok Differential Revision: D44472523 Pulled By: nateanl fbshipit-source-id: eb519b0045e7518ad13863a53271745a80d89a21
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- 16 Mar, 2023 1 commit
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jiyuntu-eero authored
Summary: Fix https://github.com/pytorch/audio/issues/3166. In `get_trellis` method, the index of blank symbol is regarded as 0 by default. It should be changed to `blank_id`. Pull Request resolved: https://github.com/pytorch/audio/pull/3172 Reviewed By: mthrok Differential Revision: D44090889 Pulled By: nateanl fbshipit-source-id: d119f4ded895d31aeefd59f8d975224870100264
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- 07 Mar, 2023 1 commit
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Maciej Torhan authored
Summary: In wav2letter example there is passed `momentum` to `Adam` and `AdamW` initializer, which is not a correct parameter. To fix that we need to add `beta_1` and `beta_2` to arguments and replace `momentum` with them. I also added `eps` similar to `Adadelta` initializer. Pull Request resolved: https://github.com/pytorch/audio/pull/3145 Reviewed By: mthrok Differential Revision: D43847713 Pulled By: nateanl fbshipit-source-id: 94f7c48232fabf520cfce81471694cb545d160c6
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- 02 Mar, 2023 1 commit
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moto authored
Summary: Fix build_doc job https://app.circleci.com/pipelines/github/pytorch/audio/15217/workflows/ce50b317-a59e-4741-b8d2-59129420deb8 - build.ffmpeg.html might not exist when IPython notebook is processed. Changing to main doc URL. - Fix bash cell syntax in HW tutorial - Fix C++ doc - Fix duplicated target name in streamwriter tutorial Pull Request resolved: https://github.com/pytorch/audio/pull/3125 Reviewed By: xiaohui-zhang Differential Revision: D43724078 Pulled By: mthrok fbshipit-source-id: ea7d46ec5e377cf2fbd7c3798df57da73750ac5c
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- 24 Feb, 2023 2 commits
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Vladislav Agafonov authored
Summary: Add `Wav2Vec2DataModule` in self_supervised_learning training recipe to support Wav2Vec2 pre-training. Pull Request resolved: https://github.com/pytorch/audio/pull/3081 Reviewed By: mthrok Differential Revision: D43579239 Pulled By: nateanl fbshipit-source-id: 3e935eb9a18ef0259a58940ae466cbdc3baf8494
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Vladislav Agafonov authored
Summary: Add wav2vec2 loss function in the self_supervised_learning training recipe to support Wav2Vec2 pre-training. Pull Request resolved: https://github.com/pytorch/audio/pull/3090 Reviewed By: mthrok Differential Revision: D43579220 Pulled By: nateanl fbshipit-source-id: 4b52792b518ddc5b01c9660c90ceb3c4ad1f0237
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- 23 Feb, 2023 1 commit
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G. Sun authored
Summary: This commit adds the implementation of the tree-constrained pointer generator (TCPGen) for contextual biasing. An example for Librispeech can be found in audio/examples/asr/librispeech_biasing. Maintainer's note (mthrok): It seems that TrieNode should be better typed as tuple, but changing the implementation from list to tuple could cause some issue without running the code, so the code is not changed, though the annotation uses tuple. Pull Request resolved: https://github.com/pytorch/audio/pull/2890 Reviewed By: nateanl Differential Revision: D43171447 Pulled By: mthrok fbshipit-source-id: 372bb077d997d720401dbf2dbfa131e6a958e37e
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- 16 Feb, 2023 2 commits
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Zhaoheng Ni authored
Summary: The `BucketizeBatchSampler` may return different iter_list in different node if `shuffle` is `True`, which will cause DPP training hang forever. `shuffle` in `DistributedSampler` only happens in initialization, which means it will assign the same subset to replicas in all training epochs. The PR fixes the two above issues. cc arlofaria Pull Request resolved: https://github.com/pytorch/audio/pull/3068 Reviewed By: mthrok Differential Revision: D43372110 Pulled By: nateanl fbshipit-source-id: a162728406ae995e05d2a07cfc2444fb76cf345e
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Zhaoheng Ni authored
Summary: In https://github.com/pytorch/audio/issues/2873, layer normalization is applied to waveforms for SSL models trained on large scale datasets. The word error rate is significantly reduced after the change. The PR updates the results for the affected models. Without the change in https://github.com/pytorch/audio/issues/2873, here is the WER result table: | Model | dev-clean | dev-other | test-clean | test-other | |:------------------------------------------------------------------------------------------------|-----------:|-----------:|-----------:|-----------:| | [WAV2VEC2_ASR_LARGE_LV60K_10M](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_10M.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_10M) | 10.59| 15.62| 9.58| 16.33| | [WAV2VEC2_ASR_LARGE_LV60K_100H](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_100H.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_100H) | 2.80| 6.01| 2.82| 6.34| | [WAV2VEC2_ASR_LARGE_LV60K_960H](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_960H.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_960H) | 2.36| 4.43| 2.41| 4.96| | [HUBERT_ASR_LARGE](https://pytorch.org/audio/main/generated/torchaudio.pipelines.HUBERT_ASR_LARGE.html#torchaudio.pipelines.HUBERT_ASR_LARGE) | 1.85| 3.46| 2.09| 3.89| | [HUBERT_ASR_XLARGE](https://pytorch.org/audio/main/generated/torchaudio.pipelines.HUBERT_ASR_XLARGE.html#torchaudio.pipelines.HUBERT_ASR_XLARGE) | 2.21| 3.40| 2.26| 4.05| After applying layer normalization, here is the updated result: | Model | dev-clean | dev-other | test-clean | test-other | |:------------------------------------------------------------------------------------------------|-----------:|-----------:|-----------:|-----------:| | [WAV2VEC2_ASR_LARGE_LV60K_10M](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_10M.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_10M) | 6.77| 10.03| 6.87| 10.51| | [WAV2VEC2_ASR_LARGE_LV60K_100H](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_100H.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_100H) | 2.19| 4.55| 2.32| 4.64| | [WAV2VEC2_ASR_LARGE_LV60K_960H](https://pytorch.org/audio/main/generated/torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_960H.html#torchaudio.pipelines.WAV2VEC2_ASR_LARGE_LV60K_960H) | 1.78| 3.51| 2.03| 3.68| | [HUBERT_ASR_LARGE](https://pytorch.org/audio/main/generated/torchaudio.pipelines.HUBERT_ASR_LARGE.html#torchaudio.pipelines.HUBERT_ASR_LARGE) | 1.77| 3.32| 2.03| 3.68| | [HUBERT_ASR_XLARGE](https://pytorch.org/audio/main/generated/torchaudio.pipelines.HUBERT_ASR_XLARGE.html#torchaudio.pipelines.HUBERT_ASR_XLARGE) | 1.73| 2.72| 1.90| 3.16| Pull Request resolved: https://github.com/pytorch/audio/pull/3070 Reviewed By: mthrok Differential Revision: D43365313 Pulled By: nateanl fbshipit-source-id: 34a60ad2e5eb1299da64ef88ff0208ec8ec76e91
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- 15 Feb, 2023 1 commit
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hwangjeff authored
Summary: Updates tutorial "Audio Data Augmentation" to use two of the newly introduced data augmentation operators in beta: `torchaudio.functional.fftconvolve` and `torchaudio.functional.add_noise`. Pull Request resolved: https://github.com/pytorch/audio/pull/3062 Reviewed By: mthrok Differential Revision: D43298120 Pulled By: hwangjeff fbshipit-source-id: 09ca736a5c67242568515d600b7d31eab32c2df1
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