Use TorchAudio to Prepare Audio Data for Deep Learning

TorchAudio is a PyTorch-based toolkit for processing audio data in machine learning projects. It enables loading audio files, converting waveforms to spectrograms, standardizing audio lengths, and augmenting data with noise. Users can prepare audio for deep learning tasks like speech recognition using essential techniques such as padding, trimming, and resampling. The tutorial demonstrates how to work with the Speech Commands dataset and create custom datasets compatible with PyTorch's data loading capabilities.