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.