학술논문

Application of GM(1,1) Model to Voice Activity Detection
Document Type
Conference
Source
2006 IEEE International Conference on Systems, Man and Cybernetics Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on. 1:770-774 Oct, 2006
Subject
Computing and Processing
Robotics and Control Systems
Additive noise
Speech enhancement
Signal to noise ratio
Frequency domain analysis
Frequency estimation
Noise generators
Signal generators
Testing
Statistics
Filters
Language
ISSN
1062-922X
Abstract
In this paper, a novel approach to apply GM(1,1) model in voice activity detection (VAD) is presented. The approach is termed as grey VAD (GVAD). In GVAD, the GM(1,1) model is used to estimate non-stationary noise in noisy speech and therefore signal component where an additive signal model is assumed. By estimated noise and signal, the signal-to-noise ratio (SNR) is calculated. Based on an adaptive threshold, the speech and non-speech segments are determined. The proposed GVAD is performed in the time domain and thus has less computational complexity than those frequency domain approaches. Through simulation, the GVAD is verified by cases with non-stationary noise. The result indicates that the proposed GVAD is able to detect voice activity appropriately.