Earticle

초록

영어

In this brief, a novel pathological continuous speech detection method based on time domain features weighted. First, different optimal threshold for time domain features, including zero crossing ratio, short-time energy and autocorrelation, are obtained from training speech data. Second, a difference evaluation technique is proposed, and with it, the difference of the same time domain feature selected from testing speech data and training speech data were obtained. Finally, to distinguish a given speech well, a novel weighting method based on difference evaluation for each kinds of time domain is employed, respectively. Experiments were conducted on the pathological speech database to prove the power and effectiveness of the proposed method. Results obtained shown that this method outperforms other early proposed time domain feature method, creating a more reliable technique for pathological continuous speech detection.

목차

Abstract
 1. Introduction
 2. Time Domain Features Introduction
  2.1. Short-Time Energy (STE)
  2.2. Zero Crossing Rate (ZCR)
  2.3. Short-Time Auto Correlation (STAC)
  2.4. Short-Time Magnitude (STM)
 3. Algorithm Description
  3.1. Time-domain Feature Template Building
  3.2. Threshold Obtained by EER Analysis
  3.3. Weighting Factor
 4. Experiment and Analysis
  4.1. Experimental Setup
  4.2. Results and Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• He Jun [ Guangdong Province Key Lab of Petrochemical Equipment Fault Diagnosis Guangdong University Petrochemical Technology Maoming City, Guangdong province, China ]
• Ji-chen Yang [ South China University of Technology School of Electronic and Information Engineering, Guangzhou, China ]
• Qing-hua Zhang [ Guangdong Province Key Lab of Petrochemical Equipment Fault Diagnosis Guangdong University Petrochemical Technology Maoming City, Guangdong province, China ]
• Guo-xi Sun [ Guangdong Province Key Lab of Petrochemical Equipment Fault Diagnosis Guangdong University Petrochemical Technology Maoming City, Guangdong province, China ]
• Jian-bing Xiong [ Guangdong Province Key Lab of Petrochemical Equipment Fault Diagnosis Guangdong University Petrochemical Technology Maoming City, Guangdong province, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605