期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2016
卷号：14
期号：2A
页码：357-362
DOI：10.12928/telkomnika.v14i2A.4378
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Voiceprint recognition is a kind of temperament recognition. It achieves judgment of temperament through analysis of voiceprint. The traditional judgment method usually recognizes the voiceprint directly, ignoring the influence of environmental noise, sound variation and other factors in the process of recognition. Study on the method of temperament accuracy judgment and intelligent processing based on voiceprint recognition is proposed because the traditional method is of low accuracy. The process includes, extraction of voiceprint main features, pretreatment of voiceprint for feature parameters, classification of the voiceprint according to the feature parameters, getting the temperament feature value through the Mel frequency cepstrum coefficient method, building the vector quantization model, introducing hypersphere extremum method to extract the sound signal features, applying LBG algorithm to classify the sound signal features, and achieving the aim of judging the temperament accurately. The experimental results show that the improved algorithm can effectively overcome the environmental noise, effectively reduce the impact of noise and sound variation, and improve the accuracy of temperament judgment.
其他摘要：Voiceprint recognition is a kind of temperament recognition. It achieves judgment of temperament through analysis of voiceprint. The traditional judgment method usually recognizes the voiceprint directly, ignoring the influence of environmental noise, sound variation and other factors in the process of recognition. Study on the method of temperament accuracy judgment and intelligent processing based on voiceprint recognition is proposed because the traditional method is of low accuracy. The process includes, extraction of voiceprint main features, pretreatment of voiceprint for feature parameters, classification of the voiceprint according to the feature parameters, getting the temperament feature value through the Mel frequency cepstrum coefficient method, building the vector quantization model, introducing hypersphere extremum method to extract the sound signal features, applying LBG algorithm to classify the sound signal features, and achieving the aim of judging the temperament accurately. The experimental results show that the improved algorithm can effectively overcome the environmental noise, effectively reduce the impact of noise and sound variation, and improve the accuracy of temperament judgment.
