This contribution presents and analyses an algorithm for the enhancement of noisy speech signals by means of spectral subtraction. In contrast to the standard spectral subtraction algorithm the proposed method does not need a speech activity detector nor histograms to learn signal statistics. The algorithm is capable to track non stationary noise signals and compares favorably with standard spe...

It is very important to capture distant-talking speech with high quality for teleconferencing systems or voice-controlled systems. For this purpose, microphone array steering and Fourier spectral subtraction, for example, are ideal candidates. A combination technique using both microphone array steering and Fourier spectral subtraction has also been proposed to improve performance. However, it ...

The corruption of speech due to presence of additive background noise causes severe difficulties in various communication environments. This paper presents a novel noise reduction technique based upon a combination of cascaded spectral subtraction and minimum mean-square error short-time log-spectral amplitude estimator methods in the wavelet domain. The scheme’s performance is illustrated by e...

Spectral subtraction based speech enhancement methods are known to be effective for the suppression of additive stationary, broadband noise. Tonal noises such as car horn sounds are found to cause serious degradation of the output speech quality. A method is proposed in this work that incorporates RASTA processing within the framework of spectral subtraction in order to achieve better suppressi...

An important concern in speaker recognition is the performance degradation that occurs when speaker models trained with speech from one type of channel are subsequently used to score speech from another type of channel, known as channel mismatch. This paper investigates the relative performance of two different spectral subtraction methods for additive noise compensation in the context of speak...

The basic problem suffered by a communication system is in the removal of additive background noise. Spectral Subtraction method (SSM) has been successfully implemented to suppress the background noise. This paper proposed a novel hybrid system for enhancing noise-corrupted speech which involves a parallel combination of Spectral Subtraction and soft thresholding method in wavelet domain for sp...

The process of suppressing the back ground noise in speech signals can be improved by subtraction of an estimate of the average noise spectrum from the noisy signal spectrum. The main objective of this paper is to implement and evaluate speech enhancement techniques based on spectral subtraction methods in presence of noise. The two techniques discussed in this paper are spectral subtraction fi...

In this paper, we propose a new technique of filter bank subtraction for robust speech recognition under various acoustic conditions. Spectral subtraction is a simple and useful technique for reducing the influence of additive noise. Conventional spectral subtraction assumes accurate estimation of the noise spectrum and no correlation between speech and noise. Those assumptions, however, are ra...

This paper addresses the problem of speech recognition in the presence of additive noise. To deal with this problem, it is possible to estimate the noise characteristics using methods which have previously been developed for speech enhancement techniques. Spectral subtraction can then be used to reduce the effect of additive noise on speech in the spectral domain. Some techniques have also rece...

A method of alleviating processing distortion caused by spectral subtraction is presented. It is well known that the spectral subtraction introduces annoying artifacts, which are referred to as undesirable musical noise, in the enhanced speech. The enhancement quality of the spectral subtraction quite depends on the performance of reducing the musical noise. Our approach exploits an adaptive fi...