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ACOUSTIC MODEL ADAPTATION METHODS BASED ON PRONUNCIATION VARIABILITY ANALYSIS FOR ENHANCING THE RECOGNITION OF VOICE OF NON-NATIVE SPEAKER AND APPARATUSES THEREOF
ACOUSTIC MODEL ADAPTATION METHODS BASED ON PRONUNCIATION VARIABILITY ANALYSIS FOR ENHANCING THE RECOGNITION OF VOICE OF NON-NATIVE SPEAKER AND APPARATUSES THEREOF
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机译:基于发音变异性的声学模型自适应方法用于增强非母语说话人声音的识别及其装置
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摘要
The example embodiment of the present invention provides an acoustic model adaptation method for enhancing recognition performance for a non-native speaker's speech. In order to adapt acoustic models, first, pronunciation variations are examined by analyzing a non-native speaker's speech. Thereafter, based on variation pronunciation of a non-native speaker's speech, acoustic models are adapted in a state-tying step during a training process of acoustic models. When the present invention for adapting acoustic models and a conventional acoustic model adaptation scheme are combined, more-enhanced recognition performance can be obtained. The example embodiment of the present invention enhances recognition performance for a non-native speaker's speech while reducing the degradation of recognition performance for a native speaker's speech.
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