The importance of the phase information of speech signal is gathering attention. Many researches indicate system combination of the amplitude and phase features is effective for improving speaker recognition performance under noisy environments. On the other hand, speech enhancement approach is taken usually to reduce the influence of noises. However, this approach only enhances the amplitude s...

This paper demonstrates the application of the Bionic Wavelet Transform (BWT), an adaptive wavelet transform derived from a nonlinear auditory model of the cochlea, to the task of speech signal enhancement. Results, measured objectively by Signal-to-Noise ratio (SNR) and Segmental SNR (SSNR) and subjectively by Mean Opinion Score (MOS), are given for additive white Gaussian noise as well as fou...

Many short-time Fourier transform (STFT) based singlechannel speech enhancement algorithms are focused on estimating clean speech spectral amplitude from the noisy observed signal in order to suppress the additive noise. To this end, the state-of-the-art speech enhancement algorithms, employ noisy amplitude information and correspondingly a priori and a posteriori SNRs while they use no informa...

In this paper, we propose a unique approach to enhance speech signals that have been corrupted by non-stationary noises. This approach is not based on a spectral subtraction algorithm, but on an algorithm that separates the speech signal and noise signal contributions in the autocorrelation domain. We call this technique the AR-HASE speech enhancement algorithm. In this initial study, we evalua...

Speech is produced when air from the lungs passes through the throat, the vocal cords, the mouth and the nasal tract. Speech processing is the study of the speech signals and the processing methods of these signals. Speech enhancement is a technique used to reduce the background noise present in the speech signal. It simply means the improvement in intelligibility and quality of degraded speech...

Signal processing methods for speech enhancement are of vital interest for communications equipments. In particular, multichannel algorithms, which perform spatial filtering to separate signals that have overlapping frequency content but different spatial origins, are important for a wide range of applications. Two of the most popular multichannel methods are blind signal separation (BSS) and b...

This thesis focus on the theory analysis and algorithm aspects of signal subspace methods used for speech enhancement in digital speech processing The problem is approached by initially performing an analysis of subspace principles applied to speech signals in order to characterize the usefulness of de ning a signal subspace for this application The theory is formulated by means of the singular...

Many short-time Fourier transform (STFT) based singlechannel speech enhancement algorithms are focused on estimating clean speech spectral amplitude from the noisy observed signal in order to suppress the additive noise. To this end, the state-of-the-art speech enhancement algorithms, employ noisy amplitude information and correspondingly a priori and a posteriori SNRs while they use no informa...

Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction ...

Speech compression, enhancement and recognition in noisy, reverberant conditions is a challenging task. In this paper a new approach to this problem, which is developed in the framework of probabilistic random modeling. speech coding techniques are commonly used in low bit rate analysis and synthesis . Coding algorithms seek to minimize the bit rate in the digital representation of a signal wit...