Earticle

초록

영어

In this paper, class-dependent acoustic features are investigated to discriminate consonant class in dysarthric speech. In dysarthric speech, imprecise articulation causes different distortion of consonants depending on each consonant class. For this reason, discrimination of consonant class can play an important role in dysarthric speech processing as a preprocessing step. Therefore, to discriminate each consonant into one of five different classes such as stop, fricative, affricate, nasal, and glide, the discrimination is performed based on a support vector machine (SVM) is employed, which is constructed by using the class-dependent acoustic features combined with mel-frequency cepstral coefficients (MFCCs). It is shown from the discrimination experiments that an SVM using the class-dependent acoustic features relatively reduces average discrimination error rate by 7.67%, compared to that using only MFCCs.

목차

Abstract
 2. Effects of Pronunciation Variations on Consonant Class
 3. Proposed Class-Dependent Acoustic Features
  3.1. Acoustic Features for Stops
  3.2. Acoustic Features for Fricatives
  3.3. Acoustic Features for Affricates
  3.4. Acoustic Features for Nasals
  3.5. Acoustic Features for Glides
 4. SVM-Based Consonant Class Discrimination
 5. Performance Evaluation
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Woo Kyeong Seong [ School of Information and Communications Gwangju Institute of Science and Technology (GIST) ]
• Ji Hun Park [ School of Information and Communications Gwangju Institute of Science and Technology (GIST) ]

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