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| Minimum Generation Error Based Optimization of HMM Model Clustering for Speech Synthesis |
| LU Heng,LING Zhen-Hua,LEI Ming,DAI Li-Rong,WANG Ren-Hua |
iFlytek Speech Laboratory,Department of Electronic Engineering and Information Science,
University of Science and Technology of China,Hefei 230027 |
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Abstract To improve the decision tree clustering and avoid possible clustered model over-training and less-training, a minimal generation error criterion and cross-validation (CV) based minimal description length factor optimizing method is introduced. CV based generation error is calculated to optimize the scale of the decision tree. Results of both subjective and objective tests show that synthesized speech by the proposed method outperforms the synthesized speech by the baseline one system in both quality and naturalness.
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Received: 03 June 2009
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2010, Vol. 23 
