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Dimensionality reduction of baum-welch statistics for speaker recognition
Dimensionality reduction of baum-welch statistics for speaker recognition
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机译:说话人识别中的baum-welch统计量的降维
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摘要
In a speaker recognition apparatus, audio features are extracted from a received recognition speech signal, and first order Gaussian mixture model (GMM) statistics are generated therefrom based on a universal background model that includes a plurality of speaker models. The first order GMM statistics are normalized with regard to a duration of the received speech signal. The deep neural network reduces a dimensionality of the normalized first order GMM statistics, and outputs a voiceprint corresponding to the recognition speech signal.
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