Speech Enhancement Based on Spectral Subtraction and Genetic Programming

In this paper, genetic programming is applied for quality improvement of noisy speech signal. Therefore, a system including both spectral subtraction and genetic programming is implemented for speech enhancement. In the proposed method, first noise is reduced by spectral subtraction. In the next step, genetic programming trees are trained for more enhancement of noisy signal by mapping the signal obtained by spectral subtraction to clean data. The proposed hybrid method improves signal to noise ratio about 2 to 6.5 dB. Comparison of genetic programming, multi-layer perceptron neural network, spectral subtraction, and the proposed hybrid method for speech enhancement indicates that the combination of spectral subtraction and genetic programming presents much better quality for enhanced signal compared to the other methods studied in this paper.