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Recurrent Neural Network and Bionic Wavelet Transform for speech enhancement

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This paper deals with speech enhancement using Bionic Wavelet Transform (BWT) and Recurrent Neural Network (RNN). Indeed, it describes a new technique, which removes additive background noise from noisy speech. This technique can be divided into two stages: the application of BWT to the speech signals and the application of an Elman neural network to find an optimal thresholding set to remove related noise wavelet coefficients. Simulation results obtained from computation of the Signal to Noise Ratio (SNR) and the Mean Opinion Scores (MOSs) show good performance of the proposed technique in comparison with many other methods.

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