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Korvax ("korva" means "ear" in Finnish) is a Python package for audio signal processing and machine learning in JAX. Korvax is framework-agnostic; it can be used in Flax, Equinox, or any other JAX framework.

JAX is a very powerful library for signal processing related tasks because of its composable function transformations (e.g., jit, vmap, grad, pmap, etc.), and often faster than PyTorch. However, PyTorch has a lot more available packages for audio processing. Korvax aims to fill this gap for JAX by porting functionality from packages such as:

• torchaudio
• librosa
• philtorch
• nnAudio
• sot-loss

Installation

Prebuilt wheels are available on PyPI for Python 3.11+ on Linux and macOS:

pip install korvax

Korvax provides a [cuda12] option that simply makes sure that jax[cuda12] is installed:

pip install "korvax[cuda12]"

Features

Currently, Korvax provides:

• Time-frequency loss functions (MR-STFT, Spectral Optimal Transport)
• Pitch estimation algorithms
• Time-varying all-pole filtering
• Resampling
• Transforms (STFT, Mel spectrogram, MFCCs, etc.)

All features are GPU-ready and differentiable.

See the documentation in the sidebar for more details and usage examples.