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Audio manipulation with torchaudio — PyTorch Tutorials …
https://pytorch.org/tutorials/beginner/audio_preprocessing_tutorial.html
To load audio data, you can use torchaudio.load. This function accepts path-like object and file-like object. The returned value is a tuple of waveform ( Tensor) and sample rate ( int ). By default, the resulting tensor object has dtype=torch.float32 and its value range is normalized within [ …
torchaudio.models — Torchaudio 0.10.0 documentation
https://pytorch.org/audio/stable/models.html
Parameters. feature_extractor (torch.nn.Module) – Feature extractor that extracts feature vectors from raw audio Tensor.. encoder (torch.nn.Module) – Encoder that converts the audio features into the sequence of probability distribution (in negative log-likelihood) over labels.. aux (torch.nn.Module or None, optional) – Auxiliary module.If provided, the output from encoder is …
Audio Embedding Extractor — bob.learn.pytorch 0.0.4 ...
https://www.idiap.ch/software/bob/docs/bob/bob.learn.pytorch/v0.0.4/guide_audio_extractor.html
Audio Embedding Extractor ¶. Audio Embedding Extractor. This subpackage is part of bob.learn.pytorch package to extract features from an input audio using CNN models which trained with pytorch. For this purpose, you can specify your feature extractor in configuration file to be used together with the verifiy.py script from bob.bio.base.
Torchaudio Documentation — Torchaudio 0.10.0 …
https://pytorch.org/audio/stable/index.html
torchaudio. This library is part of the PyTorch project. PyTorch is an open source machine learning framework. Features described in this documentation are classified by release status: Stable: These features will be maintained long-term and there should generally be no major performance limitations or gaps in documentation.
torchaudio.transforms — Torchaudio 0.10.0 documentation
https://pytorch.org/audio/stable/transforms.html
forward (waveform: torch.Tensor) → torch.Tensor [source] ¶ Parameters. waveform (Tensor) – Tensor of audio of dimension (channels, time) or (time) Tensor of shape (channels, time) is treated as a multi-channel recording of the same event and the resulting output will be trimmed to the earliest voice activity in any channel.
torchaudio.models.wav2vec2.model — Torchaudio …
https://pytorch.org/audio/master/_modules/torchaudio/models/wav2vec2/model.html
Args: feature_extractor (torch.nn.Module): Feature extractor that extracts feature vectors from raw audio Tensor. encoder (torch.nn.Module): Encoder that converts the audio features into the sequence of probability distribution (in negative log-likelihood) over labels. mask_generator (torch.nn.Module): Mask generator that generates the mask for ...
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