西安电子科技大学学报（自然科学版）2019，Vol.46Issue(1)：86-92,7.DOI:10.19665/j.issn1001-2400.2019.01.014
融合非线性幂函数和谱减法的CFCC特征提取
CFCC feature extraction for fusion of the power-law nonlinearity function and spectral subtraction
摘要
Abstract
This paper presents an improved speech feature extraction algorithm for improving the accuracy of speech recognition in noisy environment.A New Cochlear Filter Cepstral Coefficient(NCFCC)is extracted by the power-law nonlinear function which can simulate the auditory characteristics of the human ear.Then,the spectral subtraction is introduced in the feature extraction front end to enhance the signal,and the new feature and the first order difference are composed of a mixed feature parameter,after which the combined principal component analysis is made to reduce the dimension of the hybrid feature.The final feature is used in a non-specific persons,isolated words,and small-vocabulary speech recognition system.Experimental results show that,compared with the traditional Cochlear Filter Cepstral Coefficients(CFCC)feature,the Cochlear Filter Cepstral Coefficients extracted from the power-law nonlinear function significantly improve the accuracy of speech recognition.The mixed feature parameter can achieve a better speech recognition performance than a single feature.Combined with the feature set of the principal component analysis(PCA),the recognition accuracy can reach up to 88.10％ when the signal to noise ratio(SNR)is 0dB.关键词
语音识别/非线性幂函数/耳蜗滤波倒谱系数/谱减法Key words
speech recognition/power-law nonlinearity function/cochlear filter cepstral coefficients/spectral subtraction分类
信息技术与安全科学引用本文复制引用
白静,史燕燕,薛珮芸,郭倩岩..融合非线性幂函数和谱减法的CFCC特征提取[J].西安电子科技大学学报（自然科学版）,2019,46(1):86-92,7.基金项目
山西省科技攻关(社会发展)项目(20120313013-6) （社会发展）
山西省青年科技研究基金(2013021016-1) （2013021016-1）
