• DocumentCode
    431369
  • Title

    Automatic Syllable Stress Detection Using Prosodic Features for Pronunciation Evaluation of Language Learners

  • Author

    Tepperman, Joseph ; Narayanan, Shrikanth

  • Author_Institution
    Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    1
  • fYear
    2005
  • fDate
    March 18-23, 2005
  • Firstpage
    937
  • Lastpage
    940
  • Keywords
    computational linguistics; educational aids; feature extraction; natural languages; speech recognition; vocabulary; RMS energy range; automatic syllable stress detection; expected lexical stress pattern dictionary; feature extraction; fundamental frequency slope; language learner pronunciation evaluation; language learning system; machine tutor; pronunciation errors; prosodic features; student foreign language practice; system vocabulary; Computer vision; Design engineering; Dictionaries; Humans; Laboratories; Natural languages; Speech analysis; Stress; Viterbi algorithm; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8874-7
  • Type

    conf

  • DOI
    10.1109/ICASSP.2005.1415269
  • Filename
    1415269
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=431369