Noise reduction based on adaptive β-order generalized spectral subtraction for speech enhancement

Junfeng Li, Shuichi Sakamoto, Satoshi Hongo, Masato Akagi, Yôiti Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Though spectral subtraction has widely been used for speech enhancement, the spectral order β set in spectral subtraction is generally fixed to some constants, resulting in the performance limitation to a certain degree. In this paper, we first analyze the performance of the β-order generalized spectral subtraction in terms of the gain function to highlight its dependence on the value of spectral order β. Based on the analysis results and considering the non-uniform effect of real-world noise on speech signal, we further propose an adaptive β-order generalized spectral subtraction in which the spectral order β is adaptively updated according to the signal-to-noise ratio in each critical band frame by frame as in a sigmoid function. Experimental results in various noise conditions illustrate the superiority of the proposed method with regard to the traditional spectral subtraction methods.

Original languageEnglish
Title of host publicationInternational Speech Communication Association - 8th Annual Conference of the International Speech Communication Association, Interspeech 2007
Pages577-580
Number of pages4
Publication statusPublished - 2007
Event8th Annual Conference of the International Speech Communication Association, Interspeech 2007 - Antwerp, Belgium
Duration: 2007 Aug 272007 Aug 31

Publication series

NameProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume1
ISSN (Electronic)1990-9772

Other

Other8th Annual Conference of the International Speech Communication Association, Interspeech 2007
CountryBelgium
CityAntwerp
Period07/8/2707/8/31

Keywords

  • Adaptive β-order generalized spectral subtraction
  • Sigmoid function
  • Speech enhancement

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Modelling and Simulation
  • Linguistics and Language
  • Communication

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