Variational Bayesian multi-channel robust NMF for human-voice enhancement with a deformable and partially-occluded microphone array

Yoshiaki Bando, Katsutoshi Itoyama, Masashi Konyo, Satoshi Tadokoro, Kazuhiro Nakadai, Kazuyoshi Yoshii, Hiroshi G. Okuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper presents a human-voice enhancement method for a deformable and partially-occluded microphone array. Although microphone arrays distributed on the long bodies of hose-shaped rescue robots are crucial for finding victims under collapsed buildings, human voices captured by a microphone array are contaminated by non-stationary actuator and friction noise. Standard blind source separation methods cannot be used because the relative microphone positions change over time and some of them are occasionally shaded by rubble. To solve these problems, we develop a Bayesian model that separates multichannel amplitude spectrograms into sparse and low-rank components (human voice and noise) without using phase information, which depends on the array layout. The voice level at each microphone is estimated in a time-varying manner for reducing the influence of the shaded microphones. Experiments using a 3-m hose-shaped robot with eight microphones show that our method outperforms conventional methods by the signal-to-noise ratio of 2.7 dB.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1018-1022
Number of pages5
ISBN (Electronic)9780992862657
DOIs
Publication statusPublished - 2016 Nov 28
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 2016 Aug 282016 Sep 2

Publication series

NameEuropean Signal Processing Conference
Volume2016-November
ISSN (Print)2219-5491

Other

Other24th European Signal Processing Conference, EUSIPCO 2016
CountryHungary
CityBudapest
Period16/8/2816/9/2

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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