In this paper we consider the problem of speech enhancement in real-world like conditions where multiple noises can simultaneously corrupt speech. Most of the current literature on speech enhancement focus primarily on presence of single noise in corrupted speech which is far from real-world environments. Specifically, we deal with improving speech quality in office environment where multiple s...

This paper analyzes the performance of various single channel speech enhancement systems when they are applied to automatic speech recognition (ASR) systems as a preprocessor. Until now the researches on speech enhancement algorithms have focused on improving the perceptual quality of speech signal. However, it has not been verified yet whether the improvements of the perceptual quality also in...

In this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. The new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-PSO and the shuffled sub-swarms particle optimization (SSPSO) technique. It is known that the θ-PSO algorithm has better optimization performance than standard PSO al...

in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...

Noise is an unwanted signal. One of the most common type of noise is a background noise which is always present. The paper presents speech enhancement scheme for suppression of background noise. The objective of speech enhancement is to improve the perceptual aspect such as quality and intelligibility of the processed speech. The main objective of this paper is to investigate the use of differe...

This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...