The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech

Shoko Araki*, Ryo Mukai, Shoji Makino, Tsuyoki Nishikawa, Hiroshi Saruwatari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

207 Citations (Scopus)

Abstract

Despite several recent proposals to achieve blind source separation (BSS) for realistic acoustic signals, the separation performance is still not good enough. In particular, when the impulse responses are long, performance is highly limited. In this paper, we consider a two-input, two-output convolutive BSS problem. First, we show that it is not good to be constrained by the condition T > P, where T is the frame length of the DFT and P is the length of the room impulse responses. We show that there is an optimum frame size that is determined by the trade-off between maintaining the number of samples in each frequency bin to estimate statistics and covering the whole reverberation. We also clarify the reason for the poor performance of BSS in long reverberant environments, highlighting that the framework of BSS works as two sets of frequency-domain adaptive beamformers. Although BSS can reduce reverberant sounds to some extent like adaptive beamformers, they mainly remove the sounds from the jammer direction. This is the reason for the difficulty of BSS in reverberant environments.

Original languageEnglish
Pages (from-to)109-116
Number of pages8
JournalIEEE Transactions on Speech and Audio Processing
Volume11
Issue number2
DOIs
Publication statusPublished - 2003 Mar
Externally publishedYes

Keywords

  • Blind source separation
  • Convolutive mixture
  • Frame size
  • Frequency domain
  • Independent component analysis
  • Reverberant speech

ASJC Scopus subject areas

  • Software
  • Acoustics and Ultrasonics
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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