• DocumentCode
    2957828
  • Title

    An integrated approach to robust speaker identification and speech recognition

  • Author

    Kwan, C. ; Yin, J. ; Ayhan, B. ; Chu, S. ; Liu, X. ; Puckett, K. ; Zhao, Y. ; Ho, K.C. ; Kruger, M. ; Sityar, I.

  • Author_Institution
    Signal Process. Inc., Rockville, MD
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    1635
  • Lastpage
    1639
  • Abstract
    Conventional speaker identification and speech recognition algorithms cannot deal with noisy and multiple speaker environments. For example, IBM via Voice has low recognition rates if dictation is done in a noisy environment. In order to achieve high performance in speaker identification and speech recognition, we propose an integrated approach that takes every facet of the process into account. Here we summarize some preliminary results from the application of this integrated approach to robust speaker identification and speech recognition. A real-time stand-alone software prototype has been developed to evaluate the effectiveness of the approach.
  • Keywords
    speaker recognition; real-time stand-alone software prototype; robust speaker identification; speech recognition; Cepstral analysis; Hidden Markov models; Mel frequency cepstral coefficient; Microphones; Robustness; Signal processing; Signal to noise ratio; Speech enhancement; Speech recognition; Working environment noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4634016
  • Filename
    4634016