audio

Why we included this project

TorchAudio is the audio library that ships with PyTorch, and it is built to keep audio work inside the PyTorch ecosystem rather than forcing you to hop between tools. It loads common speech and audio datasets into tensors and offers the usual transforms, MelSpectrogram, MFCC, resampling and the rest, all running on GPU and staying differentiable, so the features you compute feed straight into a training loop. The project is deliberately scoped as an ML library, not a general signal processing toolbox, which is why speech recognition and audio classification teams tend to reach for it. TorchAudio is now in maintenance mode and has dropped some redundant features, but the core data loading and transform paths remain stable and fine for everyday production use.