This paper investigates the problem of verifying the pronunciations of phonemes from continuous utterances collected from impaired children speakers engaged in a speech therapy session. A new pronunciation verification (PV) approach based on the subspace Gaussian mixture model (SGMM) is presented. A single SGMM is trained from test utterances collected from impaired and unimpaired speakers. PV ...

in this paper, a new method is presented for the detection of defects in random textures. in the training stage, the feature vectors of the normal textures’ images are extracted by using the optimal response of gabor wavelet filters, and their probability density is estimated by means of the gaussian mixture model (gmm). in the testing stage, similar to the previous stage,at  first, the feature...

a parallel hybrid system of hmm and gmm modeling techniques was implemented and used in a telephony speaker verification and identification system. spectral subtraction and weighted projection measure were used to render this system more robust against additional noise. cepstral mean subtraction method was also applied for the compensation of convolution noise due to transmission channel degrad...

This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different ...

Contents 1 Introduction 2 The R program 3 Phenology, an introduction 4 Geo-statistical modelling & analysis of phenological phases 5 Multivariate tools to visualise spatio-temporal patterns in phenology 6 Gaussian Mixture Models of geographical phenomena 7 Analysis of space-time correlations within geographical studies

in this work, thermal degradation behavior of a fuel-rich energetic mixture containing epoxy binder was studied by thrmogravimetric analysis and differential scanning calorimetry under dynamic nitrogen atmosphere at different heating rates. variation of the thermal degradation activation energy of the mixture was evaluated by differential and integral isoconversional methods via akts software p...

  Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the model have estimated by EM-algorithm.   In addition pixel labeling corresponded to each pixel of true image is made by Bayes rule. In fact, ...

We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gaussians in each state. The model is defined by vectors associated with each state with a dimension of, say, 50, together with a global mapping from this vector space to the space of parameters of the GMM. This model appea...