In this paper, we consider some researches that suggest multivariate Laplace distribution (MLD) to be a proper distribution for modeling speech signal. Here, we ...
In this paper, we consider some researches that suggest multivariate Laplace distribution (MLD) to be a proper distribution for modeling speech signal. Here, we ...
Several methods have been proposed to compensate effects of noise on recognition accuracy among these methods missing feature techniques (MFT) have shown ...
Several methods have been proposed to compensate effects of noise on recognition accuracy among these methods missing feature techniques (MFT) have shown ...
Missing: means | Show results with:means
A hidden Markov model is first trained on clean speech data to model the temporal patterns which appear in the sequences of the spectral components, ...
Reconstruction of missing features by means of multivariate Laplace distribution (MLD) for noise robust speech recognition. https://doi.org/10.1016/j.eswa ...
Missing feature approaches comprise one family of noise compensation algorithms that have shown an ability to provide robust speech recognition in low SNR ...
Missing: means | Show results with:means
Reconstruction of missing features by means of multivariate Laplace ...
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In this paper, we consider some researches that suggest multivariate Laplace distribution (MLD) to be a proper distribution for modeling speech signal. Here, we ...
Speech recognition systems perform poorly in the presence of corrupting noise. Missing feature methods attempt to compensate for the noise by removing noise ...
Missing: Laplace (MLD)
Reconstruction of missing features by means of multivariate Laplace distribution (MLD) for noise robust speech recognition ... Expert Syst. Appl. 2011.