National Tsing Hua University Institutional Repository:Automatic Pronunciation Assessment for Mandarin Chinese
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    NTHUR > College of Electrical Engineering and Computer Science > Department of Computer Science > CS Conference Papers >  Automatic Pronunciation Assessment for Mandarin Chinese

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    Title: Automatic Pronunciation Assessment for Mandarin Chinese
    Authors: Jiang-Chun Chen
    Jyh-Shing Roger Jang
    Juii-Yi Li
    Ming-Chun Wu
    Date: 2004
    Publisher: Institute of Electrical and Electronics Engineers Inc
    Keywords: GMM
    Gaussian mixture model
    hidden Markov models
    Viterbi decoding
    Abstract: This work describes the algorithms used in a prototypical software system for automatic pronunciation assessment of Mandarin Chinese. The system uses Viterbi decoding to isolate each syllable and find the log probability of a given utterance based on HMM (hidden Markov models). The isolated syllables are then sent to a GMM (Gaussian mixture model) for tone recognition. Based on the log probability and the result from tone recognition, a parametric scoring function, using a neural network, is constructed to approximate the scoring results from human experts. The experimental results demonstrate the system can consistently gives scores that are close to those from human's subjective evaluation.
    Relation Link: IEEE International Conference on Multimedia and Expo, Taipei, Taiwan, June 2004
    Appears in Collections:[Department of Computer Science] CS Conference Papers
    [Institute of Information Systems and Applications] ISA Conference Papers
    [Computer and Communication Research Center ] CCRC Conference Papers

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