MFCC and SVM based recognition of Chinese vowels

Fuhai Li, Jinwen Ma, Dezhi Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations


The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no efficient method to solve it yet. In this paper, we propose a new approach to the recognition of Chinese vowels via the support vector machine (SVM) with the Mel-Frequency Cepstral Coefficients (MFCCs) as the vowel's features. It is shown by the experiments that this method can reach a high recognition accuracy on the given vowels database and outperform the SVM with the Linear Prediction Coding Cepstral (LPCC) coefficients as the vowel's features.

Original languageEnglish (US)
Title of host publicationComputational Intelligence and Security - International Conference, CIS 2005, Proceedings
Number of pages8
StatePublished - Dec 1 2005
EventInternational Conference on Computational Intelligence and Security, CIS 2005 - Xi'an, China
Duration: Dec 15 2005Dec 19 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3802 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference on Computational Intelligence and Security, CIS 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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