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| 一种改进的基于说话者的语音分割算法 |
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卢坚1, 毛兵1, 孙正兴1, 张福炎1
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南京大学,计算机科学与技术系,江苏,南京,210093,南京大学,计算机软件新技术国家重点实验室,江苏,南京,210093
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| 摘要: |
| 语音分割是语音识别和语音文档检索等众多语音应用的基础.提出一种改进的基于说话者的语音分割算法,对GLR和BIC相结合的算法作进一步的改进:(1) 基于GLR距离方差的自适应阈值调整算法改进了不同声学特征下基于距离的语音分割算法中的阈值选取方法;(2) 引入BIC可测度概念来度量其适用范围;(3) BIC信息准则校准非冗余的候选分割点的偏差.实验结果表明,此改进算法优于原算法. |
| 关键词: 基于说话者的语音分割 贝叶斯信息准则(BIC) 一般似然比(GLR) mel-frequency cepstral coefficient (MFCC) 假设检验 |
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| 基金项目:国家自然科学基金资助项目(69903006;60073030) |
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| An Improved Speaker Based Speech Segmentation Algorithm |
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LU Jian,MAO Bing,SUN Zheng-xing,ZHANG Fu-yan
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| Abstract: |
| Speech segmentation is the foundation of some applications such as speech recognition and spoken document retrieval. An improved algorithm is proposed here which include: (1) GLR variance based threshold adaptive algorithm is to improve the threshold selection approach in speaker based speech segmentation under various acoustic environments;(2) BICs Detection Ability is referred to determine when BIC is effective;(3) Besides to verify the candidate segmentation points, BIC is used to calibrate their bias caused by GLR variance.Experimental results indicate that the improved algorithm is prior to the original one. |
| Key words: speaker-based speech segmentation Bayesian information criterion （BIC） generalized likelihood ratio （GLR） mel-frequency cepstral coefficient （MFCC） hypothesis testing |
