Speech signal enhancement using neural network and wavelet transform

Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech sig...

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Bibliographic Details
Main Authors: Daqrouq, K., Abu-Isbeih, I.N., Alfauri, M.
Format: Conference Proceeding
Language:English
Subjects:
Discrete wavelet transform
Feedforward neural networks
Feeds
Neural network
Neural networks
Neurons
Noise cancellation
Signal processing
Speech enhancement
Speech processing
Speech signal
Testing
Wavelet transforms
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Summary:Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech signals will contribute to a high degree of inaccuracy in a system that requires speech processing. This idea of noise cancellation for the speech signal was processed through the neural networks. Three methods were tested: 1. The adaptive linear neuron (ADALINE). 2. feed forward neural network enhancement method FFNN 3. wavelet transform and Adaline enhancement Method. The results obtained showed high quality due to fast processing and high signal-noise-ratio. The tested signal was enhanced 10 dB by Adaline, 3 dB by FFNN and 8 dB by Wavelet Transform and Adaline Enhancement Method.
DOI:10.1109/SSD.2009.4956823