An approach to blind source separation based on temporal structure of speech signals

Noboru Murata, Shiro Ikeda*, Andreas Ziehe

*この研究の対応する著者

研究成果: Article査読

413 被引用数 (Scopus)

抄録

In this paper, we introduce a new technique for blind source separation of speech signals. We focus on the temporal structure of the signals. The idea is to apply the decorrelation method proposed by Molgedey and Schuster in the time-frequency domain. Since we are applying separation algorithm on each frequency separately, we have to solve the amplitude and permutation ambiguity properly to reconstruct the separated signals. For solving the amplitude ambiguity, we use the matrix inversion and for the permutation ambiguity, we introduce a method based on the temporal structure of speech signals. We show some results of experiments with both artificially controlled data and speech data recorded in the real environment.

本文言語English
ページ(範囲)1-24
ページ数24
ジャーナルNeurocomputing
41
1-4
DOI
出版ステータスPublished - 2001

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 認知神経科学
  • 人工知能

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