Blind dereverberation of speech signals using independence transform matrix

Jong Hwan Lee, Soo Young Lee

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)


In the real room environment, sound source is distorted with delayed versions of itself reflected from walls. This room reverberation severely degrades the intelligibility of speech and performance of automatic speech recognition system. Blind deconvolution is to find the inverse of reverberation channel when only convolved versions of the sources are available at the receiver. However existing blind deconvolution algorithms assume that a source signal has an independent identically-distributed (IED) non-Gaussian probability density function (PDF). In this research, colored nonstationary non-IID speech signals were transformed into an IID-like signal as possible by ICA-based independence transform and the resulting signals were processed using infomax blind deconvolution algorithm for the simulated minimum-phase finite impulse response (FIR) channels. Compared to the pre-whitening method by Torkkola, the proposed method demonstrated much better performance of about 30dB signal-to-reverberant components ratio (SRR).

Original languageEnglish
Number of pages5
Publication statusPublished - 2003
Externally publishedYes
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: 2003 Jul 202003 Jul 24


OtherInternational Joint Conference on Neural Networks 2003
Country/TerritoryUnited States
CityPortland, OR

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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