Acoustic models for online blind source dekevemberation using sequential monte carlo methods

Christine Evers, James R. Hopgood, Judith Bell

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

3 Citations (Scopus)

Abstract

Reverberation and noise cause significant deterioration of audio quality and intelligibility to signals recorded in acoustic environments. Noise is usually modeled as a common signal observed in the room and independent of room acoustics. However, this simplistic model cannot necessarily capture the effects of separate noise sources at different locations in the room. This paper proposes a noise model that considers distinct noise sources whose individual acoustic impulse responses are separated into source-sensor specific and common acoustical resonances. Further to noise, the signal is distorted by reverberation. Using parametric models of the system, recursive expressions of the filtering distribution can be derived. Based on these results, a sequential Monte Carlo approach for online dereverberation and enhancement is proposed. Simulation results for speech are presented to verify the effectiveness of the model and method. ©2008 IEEE.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages4597-4600
Number of pages4
DOIs
Publication statusPublished - 2008
Event33rd IEEE International Conference on Acoustics, Speech and Signal Processing 2008 - Las Vegas, NV, USA, Las Vegas, United States
Duration: 30 Mar 20084 Apr 2008

Conference

Conference33rd IEEE International Conference on Acoustics, Speech and Signal Processing 2008
Abbreviated titleICASSP 2008
CountryUnited States
CityLas Vegas
Period30/03/084/04/08

Keywords

  • Acoustic signal processing
  • Monte Carlo
  • Speech dereverberation sequential estimation
  • Speech enhancement

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    Evers, C., Hopgood, J. R., & Bell, J. (2008). Acoustic models for online blind source dekevemberation using sequential monte carlo methods. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 4597-4600) https://doi.org/10.1109/ICASSP.2008.4518680