[PDF] Top 20 Robust Bayesian estimation for context-based speech enhancement

... Speech enhancement algorithms which employ trained models, such as codebooks [24-28], hidden Markov mod- els (HMM) [29-31], Gaussian mixture models (GMM) [32], non-negative matrix factorization (NMF) models ... See full document

... Gamma speech priors was further studied in [16] and training-based procedures using the histograms of clean speech data were proposed for the estimation of the speech STSA prior ...of ... See full document

... visual speech information within a Wiener filter to improve the noisy speech ...noisy speech, especially by reducing noise intrusiveness at the cost of signal ...video speech signals, ... See full document

... this Bayesian view also allows for a convenient illustration of the underly- ing statistical dependencies of model-based approaches by means of Bayesian ...same Bayesian network, their ... See full document

... of speech quality on the receiver side. This is achieved by MMSE estimation of unobserv- able speech samples or source-coded parameters, requir- ing a posteriori ...for robust source decoding ... See full document

... respectively. The original signal consists of the desired speech and the ambient speech noise. The noise suppression results are plotted in (c) and (d), respectively. A compari- son of these plots reveals ... See full document

... PEECH enhancement aspires to improve quality by employing a variety of speech processing ...the enhancement is to improve the speech intelligibility and/or overall perceptual quality of ... See full document

... of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy ...of speech and noise power spectra. Based on the selected noise model from the initial noise ... See full document

... automatic speech recognition (ASR) systems is feature enhancement based on an analytical dis- tortion model that describes the effects of noise on the speech ...model, speech distortion ... See full document

... mask estimation designed for dere- verberation ...ture enhancement systems; for example, a deep recurrent neural network (RNN) approach for log-spectral domain feature enhancement was recently ... See full document

... Although MWF-based extension algorithms can achieve significant noise reduction, there is always a trade-off between noise reduction and cue preserva- tion regarding directional sources and background noise. One ... See full document

... channel speech enhancement algorithms, the statistical model-based enhancement techniques have recently received much ...of speech to deduce the spectral weighting function, made use of ... See full document

... know, speech signal is present only in some frames based on short-time analysis, and only some frequency bins contain significant energy in each ...of speech signal is generally sparse. However, the ... See full document

... technique based on the transient of the a posteriori SNR was proposed by Yun- Sik and ...not robust under varying noise environments, even though it obtains a relatively good ...reduce speech dis- ... See full document

... popular speech enhancement algorithms that already exist in the ...resulting speech, and yields interesting conclusions on their relative ...a speech enhancement ...noise ... See full document

... Abstract. Bayesian Program Learning (BPL) is an important area of machine ...of Bayesian model, reasoning algorithm, based on this, a detailed review of Bayesian learning based on ... See full document

... basis- based transforms and exploited the sparsity in the basis ...the Bayesian linear unmixing formulation with SBL based relevance ...the Bayesian inference hard, but it helps in re- ... See full document

... In speech signal enhancement the types of distortions can be divided into two ...the speech signal itself and 2) the distortions that affect the background ...the speech distortion when making ... See full document

... ML, Bayesian and empirical Bayesian estimators of a new introduced parameter are ...addition, Bayesian prediction of future records, based on lower record values, is ... See full document

... inference based on summary statistics, ABC resembles ...a Bayesian framework, which allows incorporation of the priors and quantification of uncertainty by means of posterior distributions of the ...to ... See full document