Speech/nonspeech detection using minimal walsh basis functions

Authors:
Moe Pwint;Farook Sattar
Affiliations:
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Venue:
EURASIP Journal on Audio, Speech, and Music Processing
Year:
2007

Citing 5
Cited 0

Dafx: Digital Audio Effects

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

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.