A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement

被引:6
|
作者
Zhang, Yan [1 ,2 ]
Tang, Zhen-min [1 ]
Li, Yan-ping [3 ]
Luo, Yang [2 ]
机构
[1] Nanjing Univ Sci & Technol NUST, Coll Comp Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China
[2] Jinling Inst Technol, Coll Informat Technol, Nanjing 211169, Jiangsu, Peoples R China
[3] Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210046, Jiangsu, Peoples R China
来源
关键词
D O I
10.1155/2014/723643
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech enhancement block. For the feature selection and voting block, several discriminating features were employed in a voting paradigm for the consideration of reliability and discriminative power. Effectiveness of the proposed approach is compared and evaluated to other VAD techniques by using two well-known databases, namely, TIMIT database and NOISEX-92 database. Experimental results show that the proposed method performs well under a variety of noisy conditions.
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页数:8
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