• DocumentCode
    1281534
  • Title

    Hearing Is Believing: Biologically Inspired Methods for Robust Automatic Speech Recognition

  • Author

    Stern, Richard M. ; Morgan, Nelson

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • Volume
    29
  • Issue
    6
  • fYear
    2012
  • Firstpage
    34
  • Lastpage
    43
  • Abstract
    The feature extraction stage of speech recognition is important historically and is the subject of much current research, particularly to promote robustness to acoustic disturbances such as additive noise and reverberation. Biologically inspired and biologically related approaches are an important subset of feature extraction methods for ASR.
  • Keywords
    feature extraction; speech recognition; acoustic disturbances; additive noise; automatic speech recognition; biologically inspired approach; biologically inspired methods; biologically related approach; feature extraction; reverberation; Adaptation models; Auditory systems; Automatic speech recognition; Computational modeling; Feature extraction; Gaussian processes; Physiology; Speech recognition;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2012.2207989
  • Filename
    6296528
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1281534