Signal enhancement using beamforming and nonstationarity with applications to speech

Sharon Gannot, David Burshtein, Ehud Weinstein

Research output: Contribution to journalArticlepeer-review

585 Scopus citations


We consider a sensor array located in an enclosure, where arbitrary transfer functions (TFs) relate the source signal and the sensors. The array is used for enhancing a signal contaminated by interference. Constrained minimum power adaptive beamforming, which has been suggested by Frost and, in particular, the generalized sidelobe canceler (GSC) version, which has been developed by Griffiths and Jim, are the most widely used beamforming techniques. These methods rely on the assumption that the received signals are simple delayed versions of the source signal. The good interference suppression attained under this assumption is severely impaired in complicated acoustic environments, where arbitrary TFs may be encountered. In this paper, we consider the arbitrary TF case. We propose a GSC solution, which is adapted to the general TF case. We derive a suboptimal algorithm that can be implemented by estimating the TFs ratios, instead of estimating the TFs. The TF ratios are estimated by exploiting the nonstationarity characteristics of the desired signal. The algorithm is applied to the problem of speech enhancement in a reverberating room. The discussion is supported by an experimental study using speech and noise signals recorded in an actual room acoustics environment.

Original languageEnglish
Pages (from-to)1614-1626
Number of pages13
JournalIEEE Transactions on Signal Processing
Issue number8
StatePublished - Aug 2001
Externally publishedYes


  • Beamforming
  • Nonstationarity
  • Speech enhancement


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