• DocumentCode
    2652495
  • Title

    Phoneme-less hierarchical accent classification

  • Author

    Lin, Xiaofan ; Simske, Steven

  • Author_Institution
    Hewlett-Packard Co., Palo Alto, CA, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    7-10 Nov. 2004
  • Firstpage
    1801
  • Abstract
    This paper introduces a novel accent classification method. Compared with existing methods, it has two unique features. First, it does not explicitly utilize phoneme information. Second, it is built on top of the gender classification. We have tested the proposed algorithm on datasets that are completely independent of training data. The accuracy of distinguishing American accent and British accent is 83%. We have also compared the accent classification with the gender classification in terms of accuracy and the saturation behavior with respect to length of utterance.
  • Keywords
    signal classification; speech recognition; gender classification; hierarchical accent classification; phoneme information; Cepstral analysis; Classification algorithms; Customer satisfaction; Data mining; Hidden Markov models; Milling machines; Speech recognition; Stochastic processes; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
  • Print_ISBN
    0-7803-8622-1
  • Type

    conf

  • DOI
    10.1109/ACSSC.2004.1399473
  • Filename
    1399473