Cyclic MVDR Beamforming
Implementation for
Giovanni Bologni, Martin Bo Møller, Richard Heusdens, Richard C. Hendriks.
MVDR Beamforming for Cyclostationary Processes, arXiv:2510.18391.
📄 Paper: https://arxiv.org/abs/2510.18391
💻 Code: https://github.com/Screeen/cMVDR
Description
Python implementation of the cyclic MVDR beamformer — an extension of the classic MVDR that exploits both spatial and spectral correlations to better suppress almost-periodic noise (e.g., engines, fans, musical instruments).
By exploiting correlations across microphones and frequency components, the cyclic minimum-variance distortionless-response (cMVDR) beamformer achieves improved noise reduction, especially in low signal-to-noise ratio (SNR) scenarios. The package includes tools for estimating resonant frequencies via periodogram analysis and computing optimal frequency shifts for inharmonic signals.
Applicable to speech enhancement, hearing aids, smart devices, and acoustic scene analysis.