• DocumentCode
    1909508
  • Title

    A Computer-Assist Algorithm to Detect Repetitive Stuttering Automatically

  • Author

    Junbo Zhang ; Bin Dong ; Yonghong Yan

  • Author_Institution
    Key Lab. of Speech Acoust. & Content Understanding, Inst. of Acoust., Beijing, China
  • fYear
    2013
  • fDate
    17-19 Aug. 2013
  • Firstpage
    249
  • Lastpage
    252
  • Abstract
    An algorithm to detect Chinese repetitive stuttering by computer is studied. According to the features of repetitions in Chinese stuttered speech, improvement solutions are provided based on the previous research findings. First, a multi-span looping forced alignment decoding networks is designed to detect multi-syllable repetitions in Chinese stuttered speech. Second, branch penalty factor is added in the networks to adjust decoding trend using recursive search in order to reduce the error from the complexity of the decoding networks. Finally, we rejudge the detected stutters by calculating confidence to improve the reliability of the detection result. The experimental results show that compared to previous algorithm, the proposed algorithm can improve system performance significantly, about 18% average detection error rate relatively.
  • Keywords
    medical disorders; natural language processing; search problems; signal detection; speech coding; Chinese stuttered speech; automatic repetitive stuttering detection; branch penalty factor; computer-assist algorithm; confidence calculation; error reduction; multispan looping forced alignment decoding networks; multisyllable repetition detection; recursive search; speech disorders; speech processing; Accuracy; Acoustics; Decoding; Equations; Mathematical model; Speech; Speech recognition; computer assist diagnosis; speech processing; stuttering detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing (IALP), 2013 International Conference on
  • Conference_Location
    Urumqi
  • Type

    conf

  • DOI
    10.1109/IALP.2013.32
  • Filename
    6646047