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

页码：3562 / 3566

页数：5

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