Spectral subtraction(SS) has been used for speech recognition in noisy environments. The maximum likelihood of noise mixed speech is analytically studied, which leads to the reformalization of SS. — Not only the subtraction factor used in conventional SS, but also a novel multiplication factor with elliptic integrals is used. This new SS method can be used alone or together with the conventiona...

In this work the use of noise reduction techniques for handsfree speech recognition in car environment is investigated. A set of experiments was carried out using different speech enhancement algorithms based on noise estimation. In particular, linear subtraction and MMSE estimators are considered in their various configurations, which depend on a different set of parameters. Experiments were c...

Speech is one of the ways to express ourselves naturally. So, speech can be used as a means to communicate with machines. In this work, using MATLAB as a platform isolated word recognizer is achieved. Speech signals get distorted by many kinds of noises. Hence, it is necessary to reduce the noise contained in the speech signal. This is called speech enhancement. Speech enhancement aims at impro...

The efficacy of four powerline interference suppression methods was tested for application in highresolution electrocardiogram (ECG). The goal was minimal distortion of the original signal micro-potential waveform, combined with maximum noise reduction. Simulated low amplitude His-bundle potentials were used for the evaluation. Several objective parameters were measured, such as mean square err...

A speech enhancement method based on probabilistic geometric approach to spectral subtraction (PGA) performed on short time magnitude spectrum is presented in this paper. A confidence parameter of noise estimation is introduced in the gain function of the proposed method to prevent subtraction of the overestimated and underestimated noise, which not only removes the noise e ciently but also pre...

The echo effect due to late reverberation can severely degrade speech quality and intelligibility. Prior attempts to reduce this degradation in the modulation domain used time-invariant filtering. In this paper, we show that performing minimum mean squared error spectral estimation in the modulation domain (MDMMSE) can significantly reduce the severity of audible reverberation and enhance the l...