Reducing the interference noise in a monaural noisy speech signal has been a challenging
task for many years. Compared to traditional unsupervised speech enhancement methods …

In this paper, we propose novel strategies for neutral vector variable decorrelation. Two
fundamental invertible transformations, namely, serial nonlinear transformation and parallel …

A key stage in speech enhancement is noise estimation which usually requires prior models
for speech or noise or both. However, prior models can sometimes be difficult to obtain. In …

Unseen noise estimation is a key yet challenging step to make a speech enhancement
algorithm work in adverse environments. At worst, the only prior knowledge we know about …

Conventional speech enhancement methods, based on frame, multiframe, or segment
estimation, require knowledge about the noise. This paper presents a new method that aims …

For enhancing noisy signals, machine-learning based single-channel speech enhancement
schemes exploit prior knowledge about typical speech spectral structures. To ensure a good …

Deriving a good model for multitalker babble noise can facilitate different speech processing
algorithms, eg, noise reduction, to reduce the so-called cocktail party difficulty. In the …

Abstract In speech enhancement, Gaussian Mixture Models (GMMs) can be used to model
the Probability Density Function (PDF) of the Periodograms of speech and different noise …

Speech intelligibility in noisy environments decreases with an increase in the noise power.
We hypothesize that the differences of subsequent short-term spectra of speech, which we …

This paper presents a speech enhancement approach based on analysis–synthesis
framework. An improved multi-band summary correlogram (MBSC) algorithm is proposed for …