Single-channel speech enhancement: Using recurrent neuro-fuzzy voice activity detector and spectral subtraction algorithms

Fang Chen Chuang, Jeen-Shing Wang, Li Ying Wu

Research output: Contribution to journalConference article

Abstract

This paper investigates the effectiveness of a single-channel speech enhancement system that contains spectral subtraction and voice activity detection algorithm for noise elimination. We first extract features from a noisy signal and use these features as the inputs of a recurrent neuro-fuzzy network for detecting the voice activities of the signal. Based on the detection, we describe the characteristics of the background noise of the speech segments by a minimum frequency energy (MFE) parameter and then apply spectral subtraction algorithms with the parameter to eliminate the noise. Our simulation results show that the proposed enhancement system with a nonlinear spectral subtraction algorithm has superior performance.

Original languageEnglish
Article number4811764
Pages (from-to)3057-3061
Number of pages5
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
DOIs
Publication statusPublished - 2008 Dec 1
Event2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapore
Duration: 2008 Oct 122008 Oct 15

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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