Fuzzy ARTMAP technique for speech noise reduction

Authors:
Boonruang Marungsri;Anant Oonsivilai
Affiliations:
School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Muang District, Nakhon Ratchasima, Thailand;School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Muang District, Nakhon Ratchasima, Thailand
Venue:
SSIP'07 Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing
Year:
2007

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Abstract

This paper presents an approach to reduction noise of speech voice commanded automatic wheel chair using a technique based on the fuzzy ARTMAP neural network (FAMNN). The measurable output noisy speech with 5dB, 1dB, -1dB, -5dB and -10dB SNR level is obtained as the contaminated signal of the interference to compare with the output data of the filter. The white noise source is acquired as the input. Finally, after training, the fuzzy ARTMAP output (i.e. estimated interference) was demonstrated. Then the estimated information signal is calculated as the difference between the measured signal and the estimated interference. The fuzzy ARTMAP could do a practically superior situation in adaptive de-noising of a speech voice commanded automatic wheel chair system with nonlinear characteristics.