Reference Microphone Selection for the Weighted Prediction Error Algorithm using the Normalized L-p Norm

TL;DR

This paper introduces a method for selecting the optimal reference microphone in the WPE dereverberation algorithm by using the normalized L-p norm of the output, improving performance in reverberant environments.

Contribution

It proposes a novel reference microphone selection technique based on the normalized L-p norm, enhancing dereverberation effectiveness for spatially distributed microphones.

Findings

The proposed method outperforms traditional selection criteria.

Improved dereverberation results across different source positions.

Effective in reverberant laboratory conditions.

Abstract

Reverberation may severely degrade the quality of speech signals recorded using microphones in a room. For compact microphone arrays, the choice of the reference microphone for multi-microphone dereverberation typically does not have a large influence on the dereverberation performance. In contrast, when the microphones are spatially distributed, the choice of the reference microphone may significantly contribute to the dereverberation performance. In this paper, we propose to perform reference microphone selection for the weighted prediction error (WPE) dereverberation algorithm based on the normalized $\ell_p$-norm of the dereverberated output signal. Experimental results for different source positions in a reverberant laboratory show that the proposed method yields a better dereverberation performance than reference microphone selection based on the early-to-late reverberation ratio or signal power.