• DocumentCode
    454752
  • Title

    Word Independent Model for Syllable Stress Evaluation

  • Author

    Verma, Ashish ; Lal, Kunal ; Lo, Yuen Yee ; Basak, Jayanta

  • Author_Institution
    IBM India Res. Lab
  • Volume
    1
  • fYear
    2006
  • fDate
    14-19 May 2006
  • Abstract
    Analyzing syllable stress in spoken English has been an area of research for a long time. In this paper, we analyze the performance of a novel method for evaluating syllable stress in spoken English. Specifically, we study the problem of determining if a word is spoken with the correct syllable stress pattern. The proposed method uses generalized models for stressed and unstressed syllables to analyze the constituent syllables of a word and determines if the word is spoken correctly. The performance of the proposed method is reported in terms of classification results on human labeled word utterances and it is compared with that of the word-dependent models using various classifiers
  • Keywords
    signal classification; speech processing; classifiers; human labeled word utterances; spoken English; syllable stress evaluation; syllable stress pattern; word independent model; word-dependent models; Humans; Loudspeakers; Mel frequency cepstral coefficient; Natural languages; Neural networks; Performance analysis; Predictive models; Speech synthesis; Stress; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • Conference_Location
    Toulouse
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1660251
  • Filename
    1660251