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Voice Recognition using Distributed Artificial Neural Network for Multiresolution Wavelet Transform

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Abstract

Voice Recognition using Distributed Artificial Neural Network for Multiresolution Wavelet Transform

Decomposition

Bandhit Suksiri

This paper presents a new voice recognition method named as Signal Clustering Neural Network by simple ANN model with a single channel microphone and Wavelet Transform feature extractions, which is achieved to increase the high recognition rates up to 95 per cent instead of Short-time Fourier Transform feature extractions at noises up to 70 dB as in the normal conversation background noises. The performance evalua- tion has been demonstrated in terms of correct recognition rate, maximum noise power of interfering sounds, Receiver Operating Characteristic and Detection Error Tradeoff curves. The proposed method offers a potential alternative to intelligence voice recog- nition system in computational linguistics and speech controlled robot application.

key words Discrete Wavelet Transform, Voice Recognition, Feature Extractions, Artificial Neural Network, Signal Clustering Neural Network.

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