Update torchaudio requirement from <=0.7.2 to <=2.0.1

[dependabot]

Updates the requirements on torchaudio to permit the latest version.

Release notes

Sourced from torchaudio's releases.

Torchaudio 2.0 Release Note

Highlights

TorchAudio 2.0 release includes:

• Data augmentation operators, e.g. convolution, additive noise, speed perturbation
• WavLM and XLS-R models and pre-trained pipelines
• Backend dispatcher powering revised info, load, save functions
• Dropped support of Python 3.7
• Added Python 3.11 support

[Beta] Data augmentation operators

The release adds several data augmentation operators under torchaudio.functional and torchaudio.transforms:

• torchaudio.functional.add_noise
• torchaudio.functional.convolve
• torchaudio.functional.deemphasis
• torchaudio.functional.fftconvolve
• torchaudio.functional.preemphasis
• torchaudio.functional.speed
• torchaudio.transforms.AddNoise
• torchaudio.transforms.Convolve
• torchaudio.transforms.Deemphasis
• torchaudio.transforms.FFTConvolve
• torchaudio.transforms.Preemphasis
• torchaudio.transforms.Speed
• torchaudio.transforms.SpeedPerturbation

The operators can be used to synthetically diversify training data to improve the generalizability of downstream models.

For usage details, please refer to the documentation for torchaudio.functional and torchaudio.transforms, and tutorial “Audio Data Augmentation”.

[Beta] WavLM and XLS-R models and pre-trained pipelines

The release adds two self-supervised learning models for speech and audio.

• WavLM that is robust to noise and reverberation.
• XLS-R that is trained on cross-lingual datasets.

Besides the model architectures, torchaudio also supports corresponding pre-trained pipelines:

• torchaudio.pipelines.WAVLM_BASE
• torchaudio.pipelines.WAVLM_BASE_PLUS
• torchaudio.pipelines.WAVLM_LARGE
• torchaudio.pipelines.WAV2VEC_XLSR_300M
• torchaudio.pipelines.WAV2VEC_XLSR_1B
• torchaudio.pipelines.WAV2VEC_XLSR_2B

For usage details, please refer to factory function and pre-trained pipelines documentation.

Backend dispatcher

Release 2.0 introduces new versions of I/O functions torchaudio.info, torchaudio.load and torchaudio.save, backed by a dispatcher that allows for selecting one of backends FFmpeg, SoX, and SoundFile to use, subject to library availability. Users can enable the new logic in Release 2.0 by setting the environment variable TORCHAUDIO_USE_BACKEND_DISPATCHER=1; the new logic will be enabled by default in Release 2.1.

# Fetch metadata using FFmpeg
metadata = torchaudio.info("test.wav", backend="ffmpeg")
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... (truncated)

Commits

• 3b40834 Change ref
• d13d8db Bump patch release (#3175)
• 11f1658 Remove references to prototype tutorials (#3171)
• 543893f Fix MFCC autograd test (#3169)
• b26f7f1 Add documentation introducing I/O backend revision (#3147)
• 6140f08 Update compatibility matrix (#3168)
• d279951 Use deterministic algorithms for filtfilt autograd tests (#3150)
• 8674f48 Fix LFCC autograd test (#3154)
• ff688de Fix linux gpu tests (#3144)
• 6dfaff1 Fix doc build (#3125) (#3137)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #542.