Torchaudio

Torchaudio

torchaudio: an audio library for PyTorch

The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension.

• Support audio I/O (Load files, Save files)
  • Load a variety of audio formats, such as wav, mp3, ogg, flac, opus, sphere, into a torch Tensor using SoX
  • Kaldi (ark/scp)
• Dataloaders for common audio datasets
• Common audio transforms
  • Spectrogram, AmplitudeToDB, MelScale, MelSpectrogram, MFCC, MuLawEncoding, MuLawDecoding, Resample
• Compliance interfaces: Run code using PyTorch that align with other libraries
  • Kaldi: spectrogram, fbank, mfcc

Installation

Please refer to https://pytorch.org/audio/main/installation.html for installation and build process of TorchAudio.

依赖pytorch，点击下面连接选择指定版本，生成安装命令： https://pytorch.org/get-started/locally/

Quick Usage

import torchaudio

waveform, sample_rate = torchaudio.load('foo.wav')  # load tensor from file
torchaudio.save('foo_save.wav', waveform, sample_rate)  # save tensor to file

Backend Dispatch

By default in OSX and Linux, torchaudio uses SoX as a backend to load and save files. The backend can be changed to SoundFile using the following. See SoundFile for installation instructions.

import torchaudio
torchaudio.set_audio_backend("soundfile")  # switch backend

waveform, sample_rate = torchaudio.load('foo.wav')  # load tensor from file, as usual
torchaudio.save('foo_save.wav', waveform, sample_rate)  # save tensor to file, as usual

Note

• SoundFile currently does not support mp3.
• "soundfile" backend is not supported by TorchScript.

API Reference

API Reference is located here: http://pytorch.org/audio/main/