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 order to the enhancement of the quality of speech corrupted by additive noise, a speech enhancement method has been put forward based on the combination of spectral subtraction and binary masking. spectral subtraction is a powerful method for removing noise from speech and binary masking provides essential elements to be used in monaural speech segregation. in the proposed combined method, f...

Enhancement of speech signal degraded by several types of noise is a topic of interest for last many years. The main aim of speech enhancement algorithm is to improve the quality and/or intelligibility of the noisy speech signals by using various techniques and algorithms. Among the all available methods, the spectral subtraction algorithm is the historically one of the first algorithm proposed...

Enhancement of speech signal degraded by additive background noise has received more attention over the past decade, due to wide range of applications and limitations of the available methods. Main objective of speech enhancement is to improve the perceptual aspects of speech such as overall quality, intelligibility and degree of listener fatigue. Among the all available methods the spectral su...

The problem of spectral subtraction, to estimate the parameters of a single source in colored noise, is used to show the relationships between the likelihood formulation and spectral density estimation. Reported previously as a filter bank processing for spectral estimation, it is shown that the normalized Capon estimate is the natural tool for source location in 1-d and 2-d scenarios when the ...

Though spectral subtraction has widely been used for speech enhancement, the spectral order β set in spectral subtraction is generally fixed to some constants, resulting in the performance limitation to a certain degree. In this paper, we first analyze the performance of the β-order generalized spectral subtraction in terms of the gain function to highlight its dependence on the value of spectr...

We propose three new adaptive noise suppression algorithms for enhancing noise-corrupted speech: smoothed spectral subtraction (SSS), vector quantization of line spectral frequencies (VQ-LSF), and modiied Wiener ltering (MWF). SSS is an improved version of the well-known spectral subtraction algorithm, while the other two methods are based on generalized Wiener ltering. We have compared these t...

The problem of enhancement of speech degraded by additive background noise has received considerable attention over the past decade. The reasons being, its wide range of applications and limitations of the available methods. Among the available single channel enhancement techniques, the spectral subtraction technique has been one of the widely adopted methods for suppressing stationary additive...