In this paper, we present a new technique for the estimation of short-term linear predictive
parameters of speech and noise from noisy data and their subsequent use in waveform …

Traditional short-time spectral attenuation (STSA) speech enhancement algorithms are
ineffective in the presence of highly nonstationary noise due to difficulties in the accurate …

Kalman filtering is a powerful technique for the estimation of a signal observed in noise that
can be used to enhance speech observed in the presence of acoustic background noise. In …

In this paper, we propose and compare various techniques for the estimation of clean
spectral envelopes in noisy conditions. The source-filter model of human speech production …

This contribution aims at speech model-based speech enhancement by exploiting the
source-filter model of human speech production. The proposed method enhances the …

We present a new codebook-based speech enhancement approach which is able to
increase robustness of conventional codebook-based approaches against model mismatch …

In this paper, we propose a Bayesian approach for the estimation of the short-term predictor
parameters of speech and noise, from the noisy observation. The resulting estimates of the …

In this paper, we propose a speech and noise auto-regressive (AR) model parameters
estimation method under noisy conditions used for speech enhancement, which exploits a …

Speech is a fundamental means of human communication. In the last several decades,
much effort has been devoted to the efficient transmission and storage of speech signals …