| VoIP压缩码流说话人识别研究 |
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| 引用本文： | 唐晖,李弼程,屈丹,张连海.VoIP压缩码流说话人识别研究[J].计算机工程,2009,35(7):180-182. |
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| 作者姓名： | 唐晖 李弼程 屈丹 张连海 |
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| 作者单位： | 解放军信息工程大学信息工程学院,郑州,450002 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 研究基于微聚类算法的VoIP压缩码流说话人识别算法。给出直接从G．729，G．723．1（6.3Kb／s），G．723．1（5．3Kb／s）压缩语音的码流中提取识别参数，以微聚类算法作为识别结构的说话人识别算法。实验结果表明，对比在压缩码流中使用同样识别参数的GMM模型，微聚类算法在识别正确率和效率上都有很大的提高。
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| 关 键 词： | 说话人识别 微聚类 压缩参数 |
| 修稿时间： | |
Research on Speaker Recognition from Compressed VoIP Packet Stream |
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| TANG Hui,LI Bi-cheng,QU Dan,ZHANG Lian-hai.Research on Speaker Recognition from Compressed VoIP Packet Stream[J].Computer Engineering,2009,35(7):180-182. |
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| Authors: | TANG Hui LI Bi-cheng QU Dan ZHANG Lian-hai |
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| Affiliation: | Institute of Information Engineering;PLA Information Engineering University;Zhengzhou 450002 |
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| Abstract: | This paper presents compressed speaker recognition approach for VoIP(Voice over IP) which is based on the micro-clustering algorithm.It designs a framework based on the micro-clustering algorithm and performs speaker recognition on the feature vector which is directly extracted from G.729, G723.1(6.3 Kb/s), G723.1(5.3 Kb/s) compressed stream.Experimental result shows that the new method is more accurate and efficient than the widely used Gaussian Mixture Model(GMM) which uses the same feature vector. |
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| Keywords: | speaker recognition micro-clustering compressed parameter |
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