doi: 10.4304/jsw.6.5.887-893
Consonant Recognition of Dysarthria Based on Wavelet Transform and Fuzzy Support Vector Machines
- 1 The First Affiliated Hospital, Jinan University, Guangzhou, China
- 2 School of Science, South China University of Technology, Guangzhou, China
Abstract
Consonant(in Chinese) recognition had important clinical significance in the assessment of dysarthria, while the consonants were so short and unstable that the recognition results of traditional methods were ineffective. The algorithm described in this paper extracted a new feature(DWTMFC-CT) of the consonants employing wavelet transformation, and the difference of similar consonants can be described more accurately by the feature. Then the algorithm classified consonants using multi-class fuzzy support vector machines(FSVM). In order to reduce the computation complexity caused by using the standard fuzzy support vector machines for multi-class classification, this paper proposed a algorithm based on two stages. Experimental results shown that the proposed algorithm could get better classification results while reducing the training time greatly.
Keywords
- wavelets transform
- fuzzy theory
- suppor
How to Cite
Zhuo-ming Chen, Wei-xin Ling, Jian-hui Zhao, and Tao-tao Yao, "Consonant Recognition of Dysarthria Based on Wavelet Transform and Fuzzy Support Vector Machines," Journal of Software, vol. 6, no. 5, pp. 887-893, 2011. https://doi.org/ 10.4304/jsw.6.5.887-893
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).