Dafx: Digital Audio Effects
Wavelet-based corner detection technique using optimal scale
Pattern Recognition Letters
Model Based Speech Pause Detection
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Exploiting Walsh-based attributes to stereo vision
IEEE Transactions on Signal Processing
A robust voice activity detector for wireless communications using soft computing
IEEE Journal on Selected Areas in Communications
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This paper presents a new method to detect speech/nonspeech components of a given noisy signal. Employing the combination of binary Walsh basis functions and an analysis-synthesis scheme, the original noisy speech signal is modified first. From the modified signals, the speech components are distinguished from the nonspeech components by using a simple decision scheme. Minimal number of Walsh basis functions to be applied is determined using singular value decomposition (SVD). The main advantages of the proposedmethod are low computational complexity, less parameters to be adjusted, and simple implementation. It is observed that the use of Walsh basis functions makes the proposed algorithm efficiently applicable in real-world situations where processing time is crucial. Simulation results indicate that the proposed algorithm achieves high-speech and nonspeech detection rates while maintaining a low error rate for different noisy conditions.