Speaker Recognition Using Composite Vector Stochastic Processes Model representation

Natalija Chmelařová, P. Chmelar, V. Tykhonov, V. M. Bezruk
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Abstract

The authors presenting a study of the automatic speaker verification for short utterances. The verification method of the speaker using word's sound parametric spectrum factorization in composite vector stochastic process representation on the base of multiplicative autoregressive model is presented in the paper. The developed method enables to receive the words features with stable characteristics for the same speaker and differ for the different speakers. The results presented in the paper showed the high correct identification probability. The features analysis for different words showed that these features also can be used in the task of connected speech recognition.
基于复合矢量随机过程模型的说话人识别
作者提出了一种短话语的自动说话人验证方法。提出了基于乘性自回归模型的复合矢量随机过程表示中的词的声音参数谱分解对说话人的验证方法。所开发的方法能够接收到对同一说话者具有稳定特征而对不同说话者具有不同特征的单词特征。结果表明,该方法具有较高的识别正确率。对不同词的特征分析表明,这些特征也可以用于连接语音识别任务。
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