HMM BASED PYRAMID MATCH KERNEL FOR CLASSIFICATION OF SEQUENTIAL PATTERNS OF SPEECH USING SUPPORT VECTOR MACHINES

被引：0
|
作者：
Dileep, A. D. [1 ]
Sekhar, C. Chandra [1 ]
机构：
[1] Indian Inst Technol, Dept Comp Sci & Engn, Madras 600036, Tamil Nadu, India
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2013年
关键词：
varying length sequences; pyramid match kernel; support vector machine; speech recognition;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Classification of varying length sequences using support vector machine (SVM) requires a suitable kernel that measures the similarity between a pair of sequences. In this paper we propose a novel approach to design a pyramid match kernel (PMK) using hidden Markov model. We study the performance of the SVM-based classifiers using the proposed PMK for recognition of isolated utterances of E-set in English alphabet and recognition of consonant-vowel segments of speech in Hindi and compare with that of the SVM-based classifiers using score-space kernels and alignments kernels.
引用
收藏
页码：3562 / 3566
页数：5
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