Ego noise reduction for hose-shaped rescue robot combining independent low-rank matrix analysis and multichannel noise cancellation

Narumi Mae*, Masaru Ishimura, Shoji Makino, Daichi Kitamura, Nobutaka Ono, Takeshi Yamada, Hiroshi Saruwatari

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

In this paper, we present an ego noise reduction method for a hose-shaped rescue robot, developed for search and rescue operations in large-scale disasters. It is used to search for victims in disaster sites by capturing their voices with its microphone array. However, ego noises are mixed with voices, and it is difficult to differentiate them from a call for help from a disaster victim. To solve this problem, we here propose a two-step noise reduction method involving the following: (1) the estimation of both speech and ego noise signals from observed multichannel signals by multichannel nonnegative matrix factorization (NMF) with the rank-1 spatial constraint, and (2) the application of multichannel noise cancellation to the estimated speech signal using reference signals. Our evaluations show that this approach is effective for suppressing ego noise.

Original languageEnglish
Title of host publicationLatent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
EditorsPetr Tichavsky, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadege Thirion-Moreau
PublisherSpringer Verlag
Pages141-151
Number of pages11
ISBN (Print)9783319535463
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017 - Grenoble, France
Duration: 2017 Feb 212017 Feb 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10169 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Country/TerritoryFrance
CityGrenoble
Period17/2/2117/2/23

Keywords

  • Environment
  • Independent vector analysis
  • Multichannel noise cancellation
  • Noise reduction
  • Nonnegative matrix factorization
  • Rescue robot
  • Tough

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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