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

应用科学学报 ›› 2019, Vol. 37 ›› Issue (1): 24-32.doi: 10.3969/j.issn.0255-8297.2019.01.003

基于MFCC与GFCC混合特征参数的说话人识别

周萍, 沈昊, 郑凯鹏

桂林电子科技大学电子工程与自动化学院, 广西桂林 541004

收稿日期:2018-02-01 修回日期:2018-04-25 出版日期:2019-01-31 发布日期:2019-01-31
作者简介:周萍,教授,研究方向:语音识别与智能控制,E-mail:940809266@qq.com
基金资助:
国家自然科学基金（No.61462017）；广西自然科学基金（No.2014GXNSFAA118353）；广西自动检测技术与仪器重点实验室基金（No.YQ15110）资助

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

摘要/Abstract

摘要：

针对说话人识别中单一参数表征不够全面的特点，将抗噪性能一般的传统MFCC参数与鲁棒性更强的GFCC参数相互融合，并结合它们的动态特性构成一种新的混合参数.针对特征参数维数过高造成的冗余，研究了每种特征参数各分量与识别结果的关系，舍弃其中贡献较低的分量以实现特征参数降维的目的，并将混合参数应用于基于高斯混合模型的说话人识别系统.仿真实验表明，该混合特征参数具有更好的识别性能和抗噪性.

关键词: Mel频率倒谱系数, 混合特征参数, Gammatone滤波器, 说话人识别

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

中图分类号:

TN912.34

周萍, 沈昊, 郑凯鹏. 基于MFCC与GFCC混合特征参数的说话人识别[J]. 应用科学学报, 2019, 37(1): 24-32.

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.

参考文献

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基于MFCC与GFCC混合特征参数的说话人识别

Speaker Recognition Based on Combination of MFCC and GFCC Feature Parameters

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