The Discrete Wavelet Transform is the most powerful and new signal compression technique which uses multiresolution analysis for analyzing speech signal. Here we are doing parallel speech compression using two different wavelet transforms like Haar wavelets and Bi-orthogonal wavelet transformation (Bior). The resultant of components which are in high frequency bands are fusioned together and di...

We present a low complexity speech enhancement technique for real-life multi-source environments. Assuming that the speaker identity is known a priori, we present the idea of incorporating speaker model to enhance a target signal corrupted in non-stationary noise in a reverberant scenario. Based on experiments, this helps to improve the limited performance of noise-tracking based speech enhance...

Compressed sensing (CS) is a kind of sampling method based on signal sparse property, it can effectively extract the signal which was contained in the message. In this study, a new noise speech enhancement method was proposed based on CS process. Voice sparsity is used to this algorithm in the discrete fast Fourier transform (Fast Fourier transform, FFT), and observation matrix is designed in c...

This paper deals with residual musical noise which results from the perceptual speech enhancement type algorithms and especially using wiener filtering approach. Perceptual speech enhancement techniques perform better than the non perceptual techniques, most of them still return a trouble residual musical noise. This is due to that only noise above the noise masking threshold (NMT) is filtered ...

In this contribution to the 3rd CHiME Speech Separation and Recognition Challenge (CHiME-3) we extend the acoustic front-end of the CHiME-3 baseline speech recognition system by a coherence-based Wiener filter which is applied to the output signal of the baseline beamformer. To compute the timeand frequency-dependent postfilter gains the ratio between direct and diffuse signal components at the...

This paper presents a novel speech enhancement approach for performing noise reduction in severely disturbed environments. A small microphone for communication purposes is placed inside the external auditory canal to pick up the speech signal originating from the speech production organ. The speech enhancement is achieved by using three different noise reduction methods: High frequencies are at...

This paper proposes a novel ICA-based MAP speech enhancement algorithm using multiple variable speech distribution models. The proposed algorithm consists of two stages, primary and advanced enhancement. The primary enhancement is performed by employing a single distribution model obtained from all speech signals. The advanced enhancement first employs multiple models of speech signals, each mo...

The performance of automatic speech recognition systems strongly decreases whenever the speech signal is disturbed by background noise. We aim to improve noise robustness focusing on all major levels of speech recognition: feature extraction, feature enhancement, and speech modeling. Different auditory modeling concepts, speech enhancement techniques, training strategies, and model architecture...

This paper deals with the impact of a signal enhancement method on speech recognition confidence scores, in the presence of noise. The speech recognition confidence score reflects the reliability of correctness of the recogniser’s output. This is important since errors in the presence of noise are more frequent and tend to make applications, such as spoken dialogue systems, too cumbersome to us...

Research has shown that degrading acoustic background noise innuences speech quality across phoneme classes in a non-uniform manner. This results in variable quality performance of many speech enhancement algorithms in noisy environments. A phoneme classiication procedure is proposed which directs single-channel constrained speech enhancement. The procedure performs broad phoneme class partitio...