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

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 ℓ<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf>-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.

Authors

Institutions

Publication Details

Published
2024-09-09
DOI
https://doi.org/10.1109/iwaenc61483.2024.10694577
Citations
1
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Simon Doclo, Toon van Waterschoot, Anselm Lohmann, Jöerg Bitzer
1 citations
Speech and Audio Processing
0.35
article

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

Simon Doclo, Toon van Waterschoot, Anselm Lohmann, Jöerg Bitzer
article en
1 citations

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 ℓ<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf>-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.

Carl von Ossietzky Universität Oldenburg (DE), Fraunhofer Institute for Digital Media Technology (DE), KU Leuven (BE)
Deutsche Forschungsgemeinschaft, KU Leuven
Openalex Percentile: Top 44%
Speech and Audio Processing
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.