Stochastic-deterministic (SD) speech modelling exploits the predictability of speech components that may be regarded deterministic. This has recently been employed in speech enhancement resulting in an improved recovery of deterministic speech components, although the improvement achieved is largely dependant on how these components are estimated. In this paper we propose a joint SD Wiener filt...

In this paper, we evaluate the performance of several objective measures in terms of predicting the quality of noisy speech enhanced by noise suppression algorithms. The objective measures considered a wide range of distortions introduced by four types of real-world noise at two SNRs by four classes of speech enhancement algorithms: spectral subtractive, subspace, statistical-model based and Wi...

The impairment factor methodology has been adopted by telecommunication experts (ITU-T, ETSI) for describing the relative impact of telephone transmission degradations on the overall quality of transmitted speech. Input parameters to this methodology are mainly instrumentally measurable characteristics of the transmission path, with the exception of low bit-rate codecs, whose perceptual charact...

A voice quality prediction method based on Gaussian mixture models (GMMs) is improved by constructing a feature selection algorithm to provide the best GMMbased prediction quality. The proposed sequential selection algorithm performs N -survivor search, allowing for trading between design complexity and performance. Simulation shows that predictors designed using the proposed algorithm outperfo...

More comparisons and analyses about the paper "Supervised Single-Channel Speech Enhancement Using Ratio Mask with Joint Dictionary Learning" mentioned are given in this document. Specifically, 1) comparisons between the clean spectra/IRM and reconstructed spectra/IRM in the training stage are done; 2) the influence of the speech dominant parameter  performed on the SNMF algorithms are shown; 3...

Submitted for the MAR05 Meeting of The American Physical Society Barkhausen Noise, Domain Structure and Entropy in Magnetic Amorphous Ribbons Under Stress ALBERTO GUIMARAES, Centro Bras. Pesq. Fisicas (CBPF), ANDRE GUNDEL, UFSM, LUCIANA SANTI, UFSM, RUBEM SOMMER, UFSM — The effect of applied stress on the magnetization process of magnetostrictive Fe78B13Si9 and amorphous Fe73.5Cu1Nb3Si13.5B9 me...

In the last few decades, many advanced technologies have been proposed, in which communications played a great role as well as telecommunications applications. The noise elimination in various environments became the most concerned as it greatly hindered the speech communication applications. The improvement of noisy speech interms of quality and intelligibility are taken into account without i...

In this paper a speech denoising strategy based on time adaptive thresholding of intrinsic modes functions (IMFs) of the signal, extracted by empirical mode decomposition (EMD), is introduced. The denoised signal is reconstructed by the superposition of its adaptive thresholded IMFs. Adaptive thresholds are estimated using the Teager-Kaiser energy operator (TKEO) of signal IMFs. More precisely,...

We examine the impact of bursty losses on the perceived quality of packet audio, and investigate the effectiveness of various approaches to improve the quality. Because the degree of burstiness depends on the packet interval, we first derive a formula to re-compute the conditional loss probability of a Gilbert loss model when the packet interval changes. We find that FEC works better at a large...

In this study, the authors propose multichannel weighted Euclidean (WE) and weighted cosh (WCOSH) cost function estimators for speech enhancement in the distributed microphone scenario. The goal of the work is to illustrate the advantages of utilising additional microphones and modified cost functions for improving signal-to-noise ratio (SNR) and segmental SNR (SSNR) along with log-likelihood r...