• DocumentCode
    898634
  • Title

    Noise compensation for speech recognition with arbitrary additive noise

  • Author

    Ming, J.

  • Author_Institution
    Sch. of Comput. Sci., Queen´´s Univ. Belfast, UK
  • Volume
    40
  • Issue
    3
  • fYear
    2004
  • Firstpage
    206
  • Lastpage
    207
  • Abstract
    A method for noise compensation for additive background noise based only on clean speech training data is described, assuming arbitrary noise characteristics. Experiments on Aurora 2 indicate that the new method has achieved a performance comparable to, or better than, the performance obtained by the baseline model trained on multi-condition data.
  • Keywords
    AWGN; probability; speech recognition; Aurora 2; additive background noise; arbitrary additive noise; arbitrary noise characteristics; baseline model; multicondition data; noise compensation; probability; speech recognition; speech training data;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:20040113
  • Filename
    1267567
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=898634