I research sound field estimation and sound field control, with a particular interest in kernel methods. Below are Python packages containing a variety of signal processing algorithms implemented in NumPy/SciPy and JAX.
Sound field estimation and sound field control
State-of-the-art methods for spatial audio processing.
Sound simulation software built on the image-source method of pyroomacoustics
Built on top of pyroomacoustics for convenient simulation of adaptive sound reproduction.
Classic signal processing toolkit
Includes time-varying MIMO filters for streaming signals, discrete Fourier transforms, adaptive filters, functions for matrices and linear systems, covariance estimation, and more.
Estimation of covariance matrices from noisy signal and noise-only data
Built on pyManopt and JAX for efficient Riemannian optimization.
Dataset for sound field estimation using moving microphones
