A Support Vector Machine-Based Voice Activity Detection Employing Effective Feature Vectors

In this letter, we propose effective feature vectors to improve the performance of voice activity detection (VAD) employing a support vector machine (SVM), which is known to incorporate an optimized nonlinear decision over two different classes. To extract the effective feature vectors, we present a novel scheme that combines the a posteriori SNR, a priori SNR, and predicted SNR, widely adopted in conventional statistical model-based VAD. key words: voice activity detection, support vector machine, a posteriori SNR, a priori SNR, predicted SNR