• DocumentCode
    178066
  • Title

    Reverberation and noise robust feature enhancement using multiple inputs

  • Author

    Shin Jae Kang ; Tae Gyoon Kang ; Kang Hyun Lee ; Kiho Cho ; Nam Soo Kim

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    1740
  • Lastpage
    1744
  • Abstract
    We propose a novel approach to feature enhancement in multi-channel scenario. Our approach is based on the interacting multiple model (IMM), which was originally developed in single-channel scenario. We extend the single-channel IMM algorithm such that it can handle the multichannel inputs under the Bayesian framework. The multichannel IMM algorithm is capable of tracking time-varying room impulse responses and background noises by updating the relevant parameters in an on-line manner. In various environmental conditions, the performance gain of the proposed method has been confirmed.
  • Keywords
    Bayes methods; acoustic signal processing; feature extraction; reverberation; speech recognition; target tracking; time-varying channels; transient response; Bayesian framework; automatic speech recognition; background noise; interacting multiple model; multichannel IMM algorithm; noise robust feature enhancement; reverberation; single channel IMM algorithm; time-varying room impulse response tracking; Microphones; Noise measurement; Reverberation; Speech; Speech recognition; Vectors; Robust speech recognition; dereverberation; interacting multiple model (IMM); multi-channel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6853896
  • Filename
    6853896