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Extraction of MFCC feature parameters based on the PCA-optimized filter bank and Korean connected 4-digit telephone speech recognition  

정성윤 (경북대학교)
김민성 (경북대학교)
손종목 (경북대학교)
배건성 (경북대학교)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.41, no.6, 2004 , pp. 279-283 More about this Journal
Abstract
In general, triangular shape filters are used in the filter bank when we extract MFCC feature parameters from the spectrum of the speech signal. A different approach, which uses specific filter shapes in the filter bank that are optimized to the spectrum of training speech data, is proposed by Lee et al. to improve the recognition rate. A principal component analysis method is used to get the optimized filter coefficients. Using a large amount of 4-digit telephone speech database, in this paper, we get the MFCCs based on the PCA-optimized filter bank and compare the recognition performance with conventional MFCCs and direct weighted filter bank based MFCCs. Experimental results have shown that the MFCC based on the PCA-optimized filter bank give slight improvement in recognition rate compared to the conventional MFCCs but fail to achieve better performance than the MFCCs based on the direct weighted filter bank analysis. Experimental results are discussed with our findings.
Keywords
PCA-optimized 필터뱅크;4연숫자 전화음성인식;MFCC특징파라미터 추출;
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