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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Li, F., Ma, J., & Huang, D. (2005). MFCC and SVM based recognition of Chinese vowels. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3802 LNAI, pp. 812–819). https://doi.org/10.1007/11596981_118
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