This paper demonstrates that modelling session variability during GMM training can improve the performance of a GMM supervector SVM speaker verification system. Recently, a method of modelling session variability in GMM-UBM systems has led to significant improvements when the training and testing conditions are subject to session effects. In this work, session variability modelling is applied d...

This study examines FDI influence on economic growth in 24 emerging market economies. The generalized Method of Moment (GMM) method is used this research using panel data to see the effect growth. also uses Panel Vector Error Correction Model (PVECM) short-term relationship and Fully Modified Ordinary Least Square (FMOLS) long-term relationship. finds strong empirical evidence indicating that s...

Dollarization has significant effects on the real sector, monetary policy, and financial system. In this study, of dollarization banks’ performance in Turkey for period 2012-2017 are investigated by using both static dynamic panel data analyses. Our Generalized Method Moments (GMM) results indicate statistical significance negative impact deposit return assets (ROA). Both random regression GMM ...

In this work, we compare the performance of three modern speaker verification systems and non-expert human listeners in the presence of voice mimicry. Our goal is to gain insights on how vulnerable speaker verification systems are to mimicry attack and compare it to the performance of human listeners. We study both traditional Gaussian mixture model-universal background model (GMM-UBM) and an i...

Gaussian mixture model (GMM) has been widely used for data analysis in various domains including text documents, face images and genes. GMM can be viewed as a simple linear superposition of Gaussian components, each of which represents a data cluster. Recent models, namely Laplacian regularized GMM (LapGMM) and locally consistent GMM (LCGMM) have been proposed to preserve the than the original ...

Based on the panel data of 18 heavy polluting industries from 34 industrial in my country as samples, empirical analysis impact environmental regulations, energy structure, enterprise scale, corporate competitiveness, and technological innovation carbon emissions industries. And by constructing a dynamic GMM model to analyze lag effect regulations emissions. The results show that: have signific...

We propose an algorithm that allows online training of a context dependent DNN model. It designs a state inventory based on DNN features and jointly optimizes the DNN parameters and alignment of the training data. The process allows flat starting a model from scratch and avoids any dependency on a GMM acoustic model to bootstrap the training process. A 15k state model trained with the proposed ...

This paper investigates the impact of stock markets and banks on economic growth using a panel data set for the period 1976-98 and applying recent GMM techniques developed for dynamic panels. On balance, we find that stock markets and banks positively influence economic growth and these findings are not due to potential biases induced by simultaneity, omitted variables or unobserved country-spe...

Image segmentation techniques are considered the main artifact against which the computer can visualize the objects in that scene and for further processing, many hand segmentation techniques are adopted in this direction which consumes the color cue as the enjoinder tools for spotting the skin pixels and non-skin pixels, GMM has been implemented successfully in this area which can tone single ...

This paper presents adaptive voice-quality control methods based on one-to-many eigenvoice conversion. To intuitively control the converted voice quality by manipulating a small number of control parameters, a multiple regression Gaussian mixture model (MR-GMM) has been proposed. The MR-GMM also allows us to estimate the optimum control parameters if target speech samples are available. However...