Wavelet and Neural Network Method for Speech Enhancement Objective Evaluation

Document Type : Original Article

Authors

1 Electronic and Communication department-Philadelphia Univ.-Jordan.

2 Arab Academy for Banking & Financial Sciences, Computer Information Systems.

3 IT Department- Gazco Company-Abu Dhabi.

4 Dhofar University, Foundation Department, Oman.

Abstract

Abstract:
Wavelet Neural Network Evaluation method WNNEM is proposed as a powerful tool
for enhanced speech signal evaluation. This objective evaluation measure utilizes Feed
forward back Propagation Neural Network FFBNN to train the free of noise signal, and
then enhanced signal is simulated to the training output results taken for given target.
The distance between simulation and the target, over different wavelet sub bands is
studied. Four known speech enhancement method for studying the performance of
WNNEM are utilized. The advantage of this method is the evaluation of different band
passes of frequency based on wavelet transform by neural network, which is very
powerful classification tool. Several objective measures are used to investigate the
WNNEM compatibility. Results proved the validity of the proposed method.

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