PSD Estimation and Source Separation in a Noisy Reverberant Environment using a Spherical Microphone Array

TL;DR

This paper introduces an efficient spherical harmonics-based method for estimating PSDs of multiple sound sources, noise, and reverberation in noisy, reverberant environments, validated with real-world microphone array data.

Contribution

It presents a novel PSD estimation technique in the spherical harmonics domain that addresses implementation issues and demonstrates robustness in practical scenarios.

Findings

Effective PSD estimation in reverberant environments

Robustness against practical deviations in microphone arrays

Improved source separation performance

Abstract

In this paper, we propose an efficient technique for estimating individual power spectral density (PSD) components, i.e., PSD of each desired sound source as well as of noise and reverberation, in a multi-source reverberant sound scene with coherent background noise. We formulate the problem in the spherical harmonics domain to take the advantage of the inherent orthogonality of the spherical harmonics basis functions and extract the PSD components from the cross-correlation between the different sound field modes. We also investigate an implementation issue that occurs at the nulls of the Bessel functions and offer an engineering solution. The performance evaluation takes place in a practical environment with a commercial microphone array in order to measure the robustness of the proposed algorithm against all the deviations incurred in practice. We also exhibit an application of the proposed PSD estimator through a source septation algorithm and compare the performance with a contemporary method in terms of different objective measures.