audio

torchaudio is a library designed to integrate PyTorch with the audio domain, focusing on data manipulation and transformation for machine learning. It provides a suite of tools for loading common audio datasets, applying standard audio transforms (such as Spectrogram, MelSpectrogram, and MFCC), and performing forced alignment for speech data. By leveraging PyTorch's tensor operations and autograd system, torchaudio ensures that all audio processing steps are differentiable and can run efficiently on GPUs. It also offers compliance interfaces to run Kaldi-compatible feature extraction. As part of the PyTorch ecosystem, it is a fundamental tool for developers and researchers building speech recognition, audio generation, and multimodal machine learning models.