Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (6): 1-5.

• Electronics, Communication & Automation Technology •     Next Articles

Detection Algorithm of Pathological Continuous Speech Based on Correlation Dimension

He Qian-hua  He Jun  Li Yan-xiong  Wang Zhi-feng   

  1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2011-11-14 Revised:2012-03-12 Online:2012-06-25 Published:2012-05-03
  • Contact: 贺前华(1965-) ，男，教授，博士生导师，主要从事语音及音频信号处理、嵌入式系统开发等的研究． E-mail:eeqhhe@scut.edu.cn
  • About author:贺前华(1965-) ，男，教授，博士生导师，主要从事语音及音频信号处理、嵌入式系统开发等的研究．
  • Supported by:

    国家自然科学基金资助项目( 60972132， 61101160) ; 广东省自然科学基金团队项目( 9351064101000003) ; 广东省自然科学基金博士科研启动项目( 10451064101004651) ; 华南理工大学中央高校基本科研业务费专项资金资助项目( 2011ZM0029)

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Abstract:

As the pre-set optimal sampling delay cannot objectively reflect the signal sampling delay and the fixed correlation dimension is inefficient in describing the complexity of pathological abnormal speech,a detection algorithm of pathological continuous speech is proposed based on correlation dimension ( CD) . In this algorithm,to avoid the defects of pre-set sampling delay,the sampling delay is continuously adjusted within a proper range of sampling delay,and an embedded CD is searched to obtain the minimum equal error rate ( EER) of normal and abnormal speech discrimination. At the same time,the correlation dimension curve is divided into several sub-intervals,and the stability of the sub-intervals is determined to overcome the drawbacks of the fixed embedded correlation dimension. After the EER analysis of the optimal CD sets of the training speech data acquired in a reasonable sampling delay range,the CD with the minimum EER and the corresponding sampling delay are chosen as the chaotic parameters of the proposed algorithm to perform a discrimination of normal and abnormal speeches. Experimental results show that the proposed algorithm possesses a correct classification rate of 75.6%,which is respectively 7. 8%,9. 3%,16.0%,18.0% and 20. 4% higher than those of the GMM-SVM algorithm,the Shimmer algorithm,the fixed CD-sampling delay algorithm,the SHR algorithm,and the Jitter algorithm.

Key words: pathological continuous speech detection, correlation dimension, delay rang, speech signal processing