This article develops a semi-supervised algorithm to address the challenging multi-source
localization problem in a noisy and reverberant environment, using a spherical harmonics …

Many single-and multi-channel speech enhancement techniques, old and new, rely in one
way or another on estimates of the noise power spectral density (PSD). For example, the …

The knowledge of speech presence probability (SPP) plays an essential role in noise
estimation and speech enhancement. Single channel SPP estimation and centralized multi …

Speech signal enhancement achieves high-level performance in recent years using deep
learning techniques. However, the deep learning technique in the speech enhancement …

This paper deals with the influence of pre-whitening for the task of fundamental frequency
estimation in noisy conditions. Parametric fundamental frequency estimators commonly …

Estimation of the noise power spectral density (PSD) plays a critical role in most existing
single-channel speech enhancement algorithms. In this paper, we present a novel noise …

The estimation of the noise power spectral density (PSD) forms a critical component of
several existing single channel speech enhancement systems. In this paper, we evaluate …

Over recent years, spatial acoustic signal processing using higher order microphone arrays
in the spherical harmonics domain has been a popular research topic. This paper uses a …

Most parametric fundamental frequency estimators make the implicit assumption that any
corrupting noise is additive, white Gaus-sian. Under this assumption, the maximum …

Several speech processing methods assume that a clean signal is observed in white
Gaussian noise (WGN). An argument against those methods is that the WGN assumption is …