Underdetermined source separation for colored sources

Stefan Winter*, Walter Kellermann, Hiroshi Sawada, Shoji Makino

*この研究の対応する著者

研究成果: Conference article査読

抄録

This contribution focuses on the source separation stage as important part of underdetermined blind source separation (BSS). So far nearly all approaches for underdetermined BSS assume independently, identically distributed (i.i.d.) sources. They completely ignore the redundancy that is in the temporal structure of colored sources like speech signals. Instead, we propose multivariate models based on the multivariate Student's t or multivariate Gaussian distribution and investigate their potential for underdetermined BSS. We provide a simple yet effective filter based on the sources' autocorrelations for recovering the sources as basis for further advances in underdetermined BSS. The challenge is estimating the filter coefficients blindly. The experimental results support the idea that source separation for underdetermined BSS can be reduced to the separation of their autocorrelations.

本文言語English
ジャーナルEuropean Signal Processing Conference
出版ステータスPublished - 2006
外部発表はい
イベント14th European Signal Processing Conference, EUSIPCO 2006 - Florence, Italy
継続期間: 2006 9月 42006 9月 8

ASJC Scopus subject areas

  • 信号処理
  • 電子工学および電気工学

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