A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement. (12th May 2014)

• Record Type: Journal Article
• Authors: Zhang, Yan; Tang, Zhen-min; Li, Yan-ping; Luo, Yang
• Other Names: Górriz Sáez Juan Manuel Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2014(2014)
• Publication Date: 2014-05-12
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2014/723643
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : 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.