Bump torchaudio from 0.13.1+cpu to 2.1.1

[dependabot]

Bumps torchaudio from 0.13.1+cpu to 2.1.1.

Release notes

Sourced from torchaudio's releases.

v2.1.1

This is a minor release, which is compatible with PyTorch 2.1.1 and includes bug fixes, improvements and documentation updates.

Bug Fixes

• Cherry-pick 2.1.1: Fix WavLM bundles (#3665)
• Cherry-pick 2.1.1: Add back compression level in i/o dispatcher backend by (#3666)

Torchaudio 2.1 Release Note

Hilights

TorchAudio v2.1 introduces the new features and backward-incompatible changes;

1. [BETA] A new API to apply filter, effects and codec
   torchaudio.io.AudioEffector can apply filters, effects and encodings to waveforms in online/offline fashion.
   You can use it as a form of augmentation.
   Please refer to https://pytorch.org/audio/2.1/tutorials/effector_tutorial.html for the examples.
2. [BETA] Tools for forced alignment
   New functions and a pre-trained model for forced alignment were added.
   torchaudio.functional.forced_align computes alignment from an emission and torchaudio.pipelines.MMS_FA provides access to the model trained for multilingual forced alignment in MMS: Scaling Speech Technology to 1000+ languages project.
   Please refer to https://pytorch.org/audio/2.1/tutorials/ctc_forced_alignment_api_tutorial.html for the usage of forced_align function, and https://pytorch.org/audio/2.1/tutorials/forced_alignment_for_multilingual_data_tutorial.html for how one can use MMS_FA to align transcript in multiple languages.
3. [BETA] TorchAudio-Squim : Models for reference-free speech assessment
   Model architectures and pre-trained models from the paper TorchAudio-Squim: Reference-less Speech Quality and Intelligibility measures in TorchAudio were added. You can use torchaudio.pipelines.SQUIM_SUBJECTIVE and torchaudio.pipelines.SQUIM_OBJECTIVE models to estimate the various speech quality and intelligibility metrics. This is helpful when evaluating the quality of speech generation models, such as TTS.
   Please refer to https://pytorch.org/audio/2.1/tutorials/squim_tutorial.html for the detail.
4. [BETA] CUDA-based CTC decoder
   torchaudio.models.decoder.CUCTCDecoder takes emission stored in CUDA memory and performs CTC beam search on it in CUDA device. The beam search is fast. It eliminates the need to move data from CUDA device to CPU when performing automatic speech recognition. With PyTorch's CUDA support, it is now possible to perform the entire speech recognition pipeline in CUDA.
   Please refer to https://pytorch.org/audio/2.1/tutorials/asr_inference_with_cuda_ctc_decoder_tutorial.html for the detail.
5. [Prototype] Utilities for AI music generation
   We are working to add utilities that are relevant to music AI. Since the last release, the following APIs were added to the prototype.
   Please refer to respective documentation for the usage.
   • torchaudio.prototype.chroma_filterbank
   • torchaudio.prototype.transforms.ChromaScale
   • torchaudio.prototype.transforms.ChromaSpectrogram
   • torchaudio.prototype.pipelines.VGGISH
6. New recipes for training models. Recipes for Audio-visual ASR, multi-channel DNN beamforming and TCPGen context-biasing were added.
   Please refer to the recipes
   • https://github.com/pytorch/audio/tree/release/2.1/examples/avsr
   • https://github.com/pytorch/audio/tree/release/2.1/examples/dnn_beamformer
   • https://github.com/pytorch/audio/tree/release/2.1/examples/asr/librispeech_conformer_rnnt_biasing
7. Update to FFmpeg support The version of supported FFmpeg libraries was updated.
   TorchAudio v2.1 works with FFmpeg 6, 5 and 4.4. The support for 4.3, 4.2 and 4.1 are dropped.
   Please refer to https://pytorch.org/audio/2.1/installation.html#optional-dependencies for the detail of the new FFmpeg integration mechanism.
8. Update to libsox integration
   TorchAudio now depends on libsox installed separately from torchaudio. Sox I/O backend no longer supports file-like object. (This is supported by FFmpeg backend and soundfile)
   Please refer to https://pytorch.org/audio/2.1/installation.html#optional-dependencies for the detail.

New Features

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Commits

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Most Recent Ignore Conditions Applied to This Pull Request

Dependency Name	Ignore Conditions
torchaudio	[>= 0.9.a, < 0.10]
torchaudio	[>= 2.0.a, < 2.1]

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[codecov-commenter]

Codecov Report

Merging #2331 (3e530cd) into main (0400813) will decrease coverage by 58.47%.
The diff coverage is n/a.

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Additional details and impacted files

@@             Coverage Diff             @@
##             main    #2331       +/-   ##
===========================================
- Coverage   85.59%   27.13%   -58.47%     
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  Files         324      324               
  Lines       29326    29325        -1     
  Branches     5407     5342       -65     
===========================================
- Hits        25101     7956    -17145     
- Misses       2842    21118    +18276     
+ Partials     1383      251     -1132     

see 257 files with indirect coverage changes

[dependabot]

Looks like torchaudio is up-to-date now, so this is no longer needed.