The rate of speech recognition can hardly be improved when it is as high as 90%, unless the speech understanding technique is used. In this paper, a new approach to Chinese speech understanding (a spelling based stochastic language model approach) is proposed and has been used to solve the problem of unrestricted speech understanding, which the classical method (rule based approach) can not. It can be used to eliminate two thirds of all the syllable errors while reducing the processing time tremendously. As a result, a Chinese speech recognition system has become commercially available.<>


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    Titel :

    Stochastic language models for Chinese speech recognition based on Chinese spelling


    Beteiligte:
    Wu Jun (Autor:in) / Wang Zuoying (Autor:in) / Ren Yansong (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    362490 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Stochastic Language Models for Chinese Speech Recognition Based on Chinese Spelling

    Wu, J. / Wang, Z. / Ren, Y. et al. | British Library Conference Proceedings | 1994


    Language Processing for Chinese Speech Recognition

    Huang, T. / Jiang, Y. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994


    Language processing for Chinese speech recognition

    Huang, T. / Jiang, Y. | IEEE | 1994


    Automatic Recognition of Arabic Sign Language Finger Spelling

    Al-Rousan, M. / Hussain, M. | British Library Online Contents | 2001


    Parallel Neural Networks for Speaker-Independent All-Chinese-Syllable Speech Recognition

    Fang, D. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994