title: A hierarchical framework approach for voice activity detection and speech enhancement.
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.
authors: College of Computer Science and Technology, Nanjing University of Science and Technology (NUST), Nanjing 210094, China ; College of Information Technology, Jinling Institute of Technology (JIT), Nanjing 211169, China.
authors: Yan
authors: Y
authors: Zhang
authors: College of Computer Science and Technology, Nanjing University of Science and Technology (NUST), Nanjing 210094, China.
authors: Zhen-min
authors: ZM
authors: Tang
authors: College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications (NUPT), Nanjing 210046, China.
authors: Yan-ping
authors: YP
authors: Li
authors: College of Information Technology, Jinling Institute of Technology (JIT), Nanjing 211169, China.
authors: Yang
authors: Y
authors: Luo
mesh_terms: D006801:Humans; D009622:Noise; D013067:Speech Perception / Q000502:physiology; D014831:Voice