[1]李燕,陶定元,林乐. 基于DTW模型补偿的伪装语音说话人识别研究[J].计算机技术与发展,2017,27(01):93-96.
　LI Yan-ping,TAO Ding-yuan,LIN Le. Study on Electronic Disguised Voice Speaker Recognition Based on DTW Model Compensation[J].,2017,27(01):93-96.
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 基于DTW模型补偿的伪装语音说话人识别研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年01期
页码:
93-96
栏目:
安全与防范
出版日期:
2017-01-10

文章信息/Info

Title:
 Study on Electronic Disguised Voice Speaker Recognition Based on DTW Model Compensation
文章编号:
1673-629X（2017)01-0093-04
作者:
 李燕; 陶定元; 林乐
 南京邮电大学 通信与信息工程学院
Author(s):
 LI Yan-ping; TAO Ding-yuan; LIN Le
关键词:
 ; 电子伪装语音; 梅尔倒谱系数; 说话人识别; 动态时间规整; 矢量量化
Keywords:
 ; electronic disguised voice; MFCC; speaker recognition; DTW; VQ
分类号:
TP302
文献标志码:
A
摘要:
 语音变声器及各种手机变声软件的出现,在提供了极其方便且丰富的娱乐交互体验的同时,也给语音通信带来了新的安全问题。由于其产生的电子伪装语音掩盖了语音本身的个性特征,对现有的说话人识别技术来说是一种挑战,且一旦被犯罪分子利用,后果将十分严重。因此,伪装语音说话人识别的研究成为当下的研究热点。提出一种针对电子伪装语音的说话人识别方法。对于由手机变声软件产生的电子伪装语音,提取该语音的梅尔倒谱系数( Mel Frequency Ceps-tral Coefficients,MFCC)作为特征参数,通过动态时间规整( Dynamic Time Warping,DTW)模型进行伪装程度鉴定,再利用矢量量化( Vector Quantization,VQ)模型进行说话人识别,从而设计了DTW与VQ相结合的电子伪装语音说话人识别系统。实验结果表明：该系统能够有效解决VQ说话人识别系统对电子伪装语音识别率过低的问题,识别效果得到了明显改善。
Abstract:
 The appearance of voice changer and various voice software of mobile phone provides a very convenient and rich entertainment interaction experience,amd at the same time,also gives voice communication new security issues. Electronic disguised voice produced masks the personality characteristics of voice itself,so the existing speaker recognition technology is a challenge,and once they are used by criminals,the consequences will be severe. Therefore,disguised voice speaker recognition is becoming a research hotspots. In view of electronic disguised voice produced by cell phone voice software,Mel Frequency Cepstral Coefficients ( MFCC) are extracted as the char-acteristic parameters of voice signals,identifying the disguised degree of it by DTW model and carrying out speaker recognition by VQ to design a speaker recognition system of electronic disguised voice. The experimental results show that the system can efficiently solve the problem that VQ has a poor recognition rate for electronic disguised voices,and improve the performance obviously.

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更新日期/Last Update: 2017-04-01