Frequency domain blind source separation for many speech signals

Ryo Mukai*, Hiroshi Sawada, Shoko Araki, Shoji Makino

*この研究の対応する著者

研究成果: Chapter

15 被引用数 (Scopus)

抄録

This paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when the number of source signals is large, and the potential source locations are omnidirectional. We propose a combination of small and large spacing sensor pairs with various axis directions in order to obtain proper geometric information for solving the permutation problem. Experimental results in a room (reverberation time TR=130 ms) with eight microphones show that the proposed method can separate a mixture of six speech signals that come from various directions, even when two of them come from the same direction.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編集者Carlos G. Puntonet, Alberto Prieto
出版社Springer Verlag
ページ461-469
ページ数9
ISBN(電子版)3540230564, 9783540230564
DOI
出版ステータスPublished - 2004
外部発表はい

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3195
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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