Robust Joint Estimation of Multi-Microphone Signal Model Parameters

TL;DR

This paper introduces a robust joint estimation method for multiple signal model parameters in multi-microphone setups, improving accuracy and performance over existing methods by using confirmatory factor analysis.

Contribution

It presents the first comprehensive method to jointly estimate all key signal model parameters, addressing inconsistencies in prior approaches.

Findings

Outperforms existing methods in parameter estimation accuracy

Achieves significant performance gains in multi-microphone applications

Demonstrates robustness across various experimental scenarios

Abstract

One of the biggest challenges in multi-microphone applications is the estimation of the parameters of the signal model such as the power spectral densities (PSDs) of the sources, the early (relative) acoustic transfer functions of the sources with respect to the microphones, the PSD of late reverberation, and the PSDs of microphone-self noise. Typically, the existing methods estimate subsets of the aforementioned parameters and assume some of the other parameters to be known a priori. This may result in inconsistencies and inaccurately estimated parameters and potential performance degradation in the applications using these estimated parameters. So far, there is no method to jointly estimate all the aforementioned parameters. In this paper, we propose a robust method for jointly estimating all the aforementioned parameters using confirmatory factor analysis. The estimation accuracy of the signal-model parameters thus obtained outperforms existing methods in most cases. We experimentally show significant performance gains in several multi-microphone applications over state-of-the-art methods.