During the past three decades, the issue of processing spectral phase has been largely
neglected in speech applications. There is no doubt that the interest of speech processing …

Recent deep neural network (DNN) based single-channel speech enhancement methods
have achieved remarkable results in the time-frequency (TF) magnitude domain. To further …

In conventional single-channel speech enhancement, typically the noisy spectral amplitude
is modified while the noisy phase is used to reconstruct the enhanced signal. Several recent …

We present a speech enhancement algorithm that performs modulation-domain Kalman
filtering to track the speech phase using circular statistics, along with the spectral log …

Within the last three decades research in single-channel speech enhancement has been
mainly focused on filtering the noisy spectral amplitude without that much focus on the …

For deep neural network (DNN)-based methods, the time-frequency (TF) masks are
commonly used as the training target. However, most of them do not focus on the phase …

In acoustical signal processing, the importance of modifying the phase spectrogram has
been shown. Recently, model-based phase recovery which is based on the sinusoidal …

Phase-aware processing has recently attracted lots of interest among researchers in speech
signal processing field as successful results have been reported for various applications …

The fundamental problem of phase-aware single-channel speech enhancement is the
estimation of the harmonic phase of signal components from noisy observations. One …

The single-channel speech enhancement problem is addressed. We propose a pitch-
adaptive short-time Fourier transform (PASTFT) framework to obtain a signal-dependent …