计算机工程与应用2016，Vol.52Issue(14)：150-155,219,7.DOI:10.3778/j.issn.1002-8331.1512-0181
多类型语音特征进化选择算法
Multiple voice features types evolutionary selection algorithm
摘要
Abstract
Speech feature extraction based on feature selection is a very effective method for speaker recognition. However, the optimal speech features have also changed. Therefore, this paper proposes a kind of four kinds of speech feature wrapper selection framework algorithm(FSF-WrGAF). The algorithm extracts four kinds of speech features, and conducts dynamic wrapper feature selection by Chainlike Agent Genetic Algorithm(CAGA)and Gaussian Mixture Model-Universal Back-ground Model(GMM-UBM), thereby obtaining high recognition accuracy. Several algorithms are compared in the experiment part. Experimental results show that the FSF-WrGAF algorithm can obtain apparent improvement in terms of accuracy, equal error rate and detection cost compared with some other algorithms.关键词
说话人识别/多类型语音特征/链式智能体遗传算法/伽马通滤波器倒谱系数(GFCC)/梅尔频率倒谱系数(MFCC)/线性预测倒谱系数(LPCC)Key words
speaker recognition/multiple voice features types/chain-like agent genetic algorithm/Gammatone Frequency Cepstrum Coefficient(GFCC)/Mel Frequency Cepstrum Coefficient(MFCC)/Linear Prediction Cepstrum Coefficient(LPCC)分类
信息技术与安全科学引用本文复制引用
张小恒,谢文宾,李勇明..多类型语音特征进化选择算法[J].计算机工程与应用,2016,52(14):150-155,219,7.基金项目
国家自然科学基金（No.91438104）；中央高校基本科研业务费专项资金（No.CDJZR10160003，No.CDJZR13160008， No.CDJZR155507）；中国博士后科学基金（No.2013M532153）；重庆市博士后科研项目特别资助。 （）
