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Speaker selection training via a-posteriori Gaussian mixture model analysis, transformation, and combination of hidden Markov models
Speaker selection training via a-posteriori Gaussian mixture model analysis, transformation, and combination of hidden Markov models
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机译:通过后验高斯混合模型分析,转换和组合隐马尔可夫模型进行说话人选择训练
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摘要
The present invention is directed to a 3-stage adaptation framework based on speaker selection training. First a subset of cohort speakers is selected for a test speaker. Then cohort models are transformed to be closer to the test speaker. Finally the adapted model for the test speaker is obtained by combining these transformed cohort models. Combination weights as well as bias items can be adaptively learned from adaptation data.
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