An LCMV Filter for Single-Channel Noise Cancellation and Reduction in the Time Domain

Jesper Rindom Jensen, Jacob Benesty, Mads Græsbøll Christensen, Jingdong Chen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)
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Abstract

In this paper, we consider a recent class of optimal rectangular fil- tering matrices for single-channel speech enhancement. This class of filters exploits the fact that the dimension of the signal subspace is lower than that of the full space. Then, extra degrees of freedom in the filters, that are otherwise reserved for preserving the signal subspace, can be used for achieving an improved output signal-to- noise ratio (SNR). Interestingly, these filters unify the ideas of opti- mal filtering and subspace methods. We propose an optimal LCMV filter in this framework with minimum output power that passes the desired signal undistorted and cancels correlated noise. The cancel- lation was not facilitated by the filters derived so far in this frame- work. The results show that the proposed filter can achieve output SNRs similar to that of competing filter designs, while having a much higher output signal-to-interference ratio. This is showed for both synthetic and real speech signals.
Original languageEnglish
Title of host publication2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
PublisherIEEE
Publication date2013
Pages1-4
DOIs
Publication statusPublished - 2013
EventWASPAA 2013 - New York, United States
Duration: 20 Oct 201323 Oct 2013

Conference

ConferenceWASPAA 2013
CountryUnited States
CityNew York
Period20/10/201323/10/2013
SeriesI E E E Workshop on Applications of Signal Processing to Audio and Acoustics
ISSN1931-1168

Keywords

  • speech enhancement
  • interferer cancellation
  • LCMV
  • Optimal filtering

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