6 accepted papers
In recent years, the introduction of neural networks (NNs) into the field of speech enhancement has brought significant improvements. However, many of the proposed methods are quite demanding in terms of computational complexity and memory footprint. For the application in dedicated communication de…
The problem of estimating the a priori signal-to-noise ratio (SNR) for single-channel speech enhancement is addressed. Similar to the decision-directed approach we linearly combine the maximum likelihood estimate of the a priori SNR with an estimate obtained from the previous frame. Based on the har…
Phase-aware signal processing has received increasing interest in many speech applications. The success of phase-aware processing depends strongly on the robustness of the clean spectral phase estimates to be obtained from a noisy observation. In this paper, we propose a novel harmonic phase estimat…
Conventional single-channel speech enhancement is mainly focused on modifying the noisy short-time Fourier transform amplitude spectrum while for signal reconstruction the noisy phase is used. Recent advances demonstrate the positive improvements in speech enhancement when the noisy phase is replace…
In single-channel speech enhancement the spectral amplitude of the noisy signal is often modified while the noisy spectral phase is directly employed for signal reconstruction. Recently, additional improvement in speech enhancement performance has been reported when the noisy phase is modified. In t…
To approximate the speech quality of a given speech enhancement system, most of the existing instrumental metrics rely on the calculation of a distortion metric defined between the clean reference signal and the enhanced signal in the spectral amplitude domain. Several recent studies have demonstrat…