Detecting tone errors in continuous Mandarin speech

  title={Detecting tone errors in continuous Mandarin speech},
  author={Yan-Bin Zhang and Min Chu and Chao Huang and Mangui Liang},
  journal={2008 IEEE International Conference on Acoustics, Speech and Signal Processing},
This paper proposes a new approach for detecting tone errors in continuous Mandarin speech. In the training phase, tone variations are modeled with context-depended MSD-HMM which considers six contextual factors instead of two in traditional triphone HMM. In the evaluation phase, the goodness of tone pronunciation is measured by Kullback-Leibler divergence (KLD) between the expected tone model and the most representative tone model. When the KLD between the two models is larger than a threshold… CONTINUE READING

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Key Quantitative Results

  • In the ROC curve, we get the equal error rate at 2.6%.


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