Gaussian model-based multichannel speech presence probability

Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofiène Affes

Research output: Contribution to journalArticlepeer-review

81 Scopus citations

Abstract

The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications including reliable noise reduction algorithms. In this correspondence, we establish a new expression for speech presence probability when an array of microphones with an arbitrary geometry is used. Our study is based on the assumption of the Gaussian statistical model for all signals and involves the noise and noisy data statistics only. In comparison with the single-channel case, the new proposed multichannel approach can significantly increase the detection accuracy. In particular, when the additive noise is spatially coherent, perfect speech presence detection is theoretically possible, while when the noise is spatially white, a coherent summation of speech components is performed to allow for enhanced speech presence probability estimation.

Original languageEnglish
Article number5299039
Pages (from-to)1072-1077
Number of pages6
JournalIEEE Transactions on Audio, Speech and Language Processing
Volume18
Issue number5
DOIs
StatePublished - 2010
Externally publishedYes

Keywords

  • Microphone array
  • Noise reduction
  • Speech detection
  • Speech presence probability

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