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The Scientific World Journal
Volume 2014, Article ID 723643, 8 pages
Research Article

A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement

1College of Computer Science and Technology, Nanjing University of Science and Technology (NUST), Nanjing 210094, China
2College of Information Technology, Jinling Institute of Technology (JIT), Nanjing 211169, China
3College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications (NUPT), Nanjing 210046, China

Received 10 February 2014; Accepted 22 April 2014; Published 12 May 2014

Academic Editor: Juan Manuel Górriz Sáez

Copyright © 2014 Yan Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.