• DocumentCode
    3130947
  • Title

    The implementation of a practical high performance Mandarin and Sichuan Dialect continuous speech recognition system for parcels checking task

  • Author

    Yixiang, Shan ; Haotian, Zhang ; Husheng, Li ; Lin, Zhong ; Jin, Zhang ; Jia, Liu ; Runsheng, Liu

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    409
  • Lastpage
    412
  • Abstract
    This paper presents a high performance real-time Mandarin and Sichuan Dialect speaker-independent continuous speech recognition system utilized for a post parcels checking task. The vocabulary of the system consists of 4500 Chinese place names and 1021 number strings. For Mandarin speech the recognition accuracies are achieved 98.9% for top-1 and 99.7% for top-3. For Sichuan Dialect speech, the recognition accuracies are achieved 98.6% for top-1 and 99.9% for top-3. Besides, the rejection method based online garbage model and speaker adaptation method are employed and integrated into the system to improve its robustness. A mixed start-end point detection algorithm is used. The system can work stably under a high-noise background environment with high performance
  • Keywords
    postal services; real-time systems; speech recognition; vocabulary; Chinese place names; Mandarin; Sichuan Dialect; continuous speech recognition system; high performance; mixed start-end point detection; online garbage model; post parcel checking; real-time system; rejection method; speaker adaptation method; speaker-independent system; vocabulary; Adaptation model; Detection algorithms; Maximum likelihood estimation; Personal digital assistants; Real time systems; Robustness; Speech recognition; Speech synthesis; Transportation; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Multimedia, Video and Speech Processing, 2001. Proceedings of 2001 International Symposium on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    962-85766-2-3
  • Type

    conf

  • DOI
    10.1109/ISIMP.2001.925420
  • Filename
    925420