This paper describes a method of compensating for nonlinear distortions in speech
representation caused by noise. The method described here is based on the histogram …

This paper presents a novel speech feature enhancement technique based on a
probabilistic, nonlinear acoustic environment model that effectively incorporates the phase …

This paper introduces a method of noise-robust automatic speech recognition (ASR) that
remains effective under one-pass single-channel processing. Under these constraints, the …

The performance of automatic speech recognition (ASR) system is often degraded in
adverse real-world environments. In recent times, deep learning has successfully emerged …

This paper presents an approach to the recognition of speech signal using frequency
spectral information with Mel frequency for the improvement of speech feature …

This article deliberates a mathematical model for the estimation of speech signals probability
density function. Speech recognition is analyzed using an integration of Boltzmann …

Hidden Markov model (HMM)-based minimum mean square error speech enhancement
method in Mel-frequency domain is focused on and a parallel cepstral and spectral (PCS) …

In this paper, we present a new algorithm for statistical speech feature enhancement in the
cepstral domain. The algorithm exploits joint prior distributions (in the form of Gaussian …

This paper presents a feature-enhancement method that uses the outputs of independent
vector analysis (IVA) for robust speech recognition. Although frequency-domain (FD) …

This paper addresses the problem of voice activity detection (VAD) in noisy environments.
The VAD method proposed in this paper is based on a statistical model approach, and …