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 sign...

In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE  estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of  noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...

background and aim: quick speech in noise (q-sin) test has popularity for evaluating speech recognition in noise. the present study has been paid to build five new persian lists with respect to all possible factors affecting the test, to determine validity of the test and to run five lists for normal hearing subjects and assessment of reliability. methods: to build lists, frequent, familiar and...

The speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. This paper discusses a novel technique for speech enhancement which is based on Singular Value Decomposition. This implementation utilizes a Genetic Algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as t...

the mel frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. in this paper to achieve a satisfactorily performance in automatic speech recognition (asr) applications we introduce a noise robust new set of mfcc vector estimated through following steps. first, spectral mean normalization is a pre-processing which applies to t...