数据采集与处理2012，Vol.27Issue(1)：51-56,6.
基于EEMD域统计模型的话音激活检测算法
Voice Activity Detection Algorithm Based on Ensemble Empirical Mode Decomposition Domain Statistical Model
摘要
Abstract
Voice activity detection algorithm based on ensemble empirical mode decomposition domain statistical model is presented. The noisy speech is decomposed into intrinsic mode function (IMF) components by using ensemble empirical mode decomposition (EEMD) method. Two IMF components with the higher correlation with original speech are added to calculate the characteristic parameter of the statistical model. The decision of the speech/noise is made by comparing the characteristic parameter with its threshold. The proposed VAD algorithm is tested on speech signals under various noise conditions with several SNRs. Experimental results show that the proposed VAD algorithm outperforms some standard VAD algorithms, especially under a low SNR noisy condition.关键词
话音激活检测/经验模式分解/总体平均经验模式分解/EEMD域统计模型Key words
voice activity detection (VAD)/ empirical mode decomposition (EMD)/ ensemble empirical mode decomposition (EEMD)/ EEMD domain statistical model分类
信息技术与安全科学引用本文复制引用
吴其前,张雄伟..基于EEMD域统计模型的话音激活检测算法[J].数据采集与处理,2012,27(1):51-56,6.基金项目
江苏省自然科学基金(BK2009059)资助项目. （BK2009059）
