• DocumentCode
    3125341
  • Title

    Hierarchical prosodic pattern selection based on Fujisaki model for natural mandarin speech synthesis

  • Author

    Yi-Chin Huang ; Chung-Hsien Wu ; Sz-Ting Weng

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan
  • fYear
    2012
  • fDate
    5-8 Dec. 2012
  • Firstpage
    79
  • Lastpage
    83
  • Abstract
    In this paper, a novel hierarchical prosodic unit selection method is proposed based on pitch contour pattern retrieval, in order to obtained natural pitch contour of the personalized synthetic voice. In this framework, a hierarchical prosodic unit based on Fujisaki model is used to take local pitch contour variation and global intonation of utterance into account. Furthermore, novel ways of integrating pitch contour pattern of prosodic units in the prosodic model are invents in order to improve the selection mechanism of the appropriate pitch contour. A novel prosodic unit selection method is proposed based on sentence retrieval, which not only uses the traditional linguistic cue as selection criterion, but also the shape of the pitch contour. Also, the codewords of pitch patterns in the training corpus and synthesized corpus were constructed by the proposed method and were used to map the relation between training codeword and synthesized corpus. Finally, the language model of pitch pattern is adopted to find the proper pitch pattern sequence of input text. The evaluation results demonstrate that the proposed prosodic model substantially improves naturalness of the intonation of the synthesized speech compared to that of model-based method.
  • Keywords
    codes; natural language processing; speech coding; speech synthesis; Fujisaki model; corpus synthesis; hierarchical prosodic pattern selection; hierarchical prosodic unit selection method; language model; local pitch contour variation; natural Mandarin speech synthesis; natural pitch contour; personalized synthetic voice; pitch contour pattern retrieval; pitch pattern; sentence retrieval; training codeword; training corpus; Hidden Markov models; Pragmatics; Speech; Speech synthesis; Training; Vectors; Fujisaki Model; Hierarchical Prosodic Structure; Pattern Retrieval; Unit Selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chinese Spoken Language Processing (ISCSLP), 2012 8th International Symposium on
  • Conference_Location
    Kowloon
  • Print_ISBN
    978-1-4673-2506-6
  • Electronic_ISBN
    978-1-4673-2505-9
  • Type

    conf

  • DOI
    10.1109/ISCSLP.2012.6423536
  • Filename
    6423536