• DocumentCode
    749447
  • Title

    A new duration modeling approach for Mandarin speech

  • Author

    Chen, Sin-Horng ; Lai, Wen-Hsing ; Wang, Yih-Ru

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    11
  • Issue
    4
  • fYear
    2003
  • fDate
    7/1/2003 12:00:00 AM
  • Firstpage
    308
  • Lastpage
    320
  • Abstract
    A new duration modeling approach for Mandarin speech is proposed. It explicitly takes several major affecting factors, such as multiplicative companding factors (CFs), and estimates all model parameters by an EM algorithm. The three basic Tone 3 patterns (i.e., full tone, half tone and sandhi tone) are also properly considered using three different CFs to separate how they affect syllable duration. Experimental results show that the variance of the syllable duration is greatly reduced from 180.17 to 2.52 frame2 (1 frame = 5 ms) by the syllable duration modeling to eliminate effects from those affecting factors. Moreover, the estimated CFs of those affecting factors agree well with our prior linguistic knowledge. Two extensions of the duration modeling method are also performed. One is the use of the same technique to model initial and final durations. The other is to replace the multiplicative model with an additive one. Lastly, a preliminary study of applying the proposed model to predict syllable duration for TTS (text-to-speech) is also performed. Experimental results show that it outperforms the conventional regressive prediction method.
  • Keywords
    linguistics; natural languages; optimisation; parameter estimation; speech processing; speech recognition; speech synthesis; EM algorithm; Mandarin speech; additive model; duration modeling approach; full tone; half tone; linguistic knowledge; multiplicative companding factors; parameter estimation; prosodic modeling; regressive prediction method; sandhi tone; speech processing; speech recognition; syllable duration; text-to-speech synthesis; Automatic speech recognition; Frequency; Natural languages; Parameter estimation; Prediction methods; Predictive models; Speech analysis; Speech recognition; Speech synthesis; Timing;
  • fLanguage
    English
  • Journal_Title
    Speech and Audio Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6676
  • Type

    jour

  • DOI
    10.1109/TSA.2003.814377
  • Filename
    1214847