基于MFCC与GFCC混合特征参数的说话人识别

doi:10.3969/j.issn.0255-8297.2019.01.003

Journal of Applied Sciences ›› 2019, Vol. 37 ›› Issue (1): 24-32.doi: 10.3969/j.issn.0255-8297.2019.01.003

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Speaker Recognition Based on Combination of MFCC and GFCC Feature Parameters

ZHOU Ping, SHEN Hao, ZHENG Kai-peng

College of Electric Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, Guangxi Province, China

Received:2018-02-01 Revised:2018-04-25 Online:2019-01-31 Published:2019-01-31

Abstract

Abstract:

Aiming at the issue that single feature parameter of speaker recognition has the shortcoming of low representation ability, a set of mixture feature parameters is formed by combining the single poor anti-noise Mel frequency cepstral coefficients (MFCC) with more robust Gammatone frequency cepstral coefficients (GFCC) and their dynamic differential in this paper. Since the high dimension of the mixture feature parameters, the relationships of each dimension of different feature parameters and recognition results is studied, where dimensionality reduction on high dimensional features is implemented by discarding the dimensions with low contribution ratio. After that, the combination of feature parameters was applied to the speaker recognition system based on Gaussian mixture model. Experimental results show that the combination of parameters can better describe the speakers' feature and have better anti-noise capability.

Key words: combination of feature parameters, Mel frequency cepstral coefficients (MFCC), speaker recognition, Gammatone filter

CLC Number:

TN912.34

ZHOU Ping, SHEN Hao, ZHENG Kai-peng. Speaker Recognition Based on Combination of MFCC and GFCC Feature Parameters[J]. Journal of Applied Sciences, 2019, 37(1): 24-32.

References

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Speaker Recognition Based on Combination of MFCC and GFCC Feature Parameters

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