Voice activity detection (VAD) is a basic component of noise reduction algorithms. In this paper, we propose a voice activity detector based on a sequential Gaussian Mixture Model (SGMM) in log-spectral domain. This model comprises two Gaussian components, which respectively describe the speech and nonspeech log-power distributions. The initial distributions are firstly established by EM algori...

In this paper, large vocabulary children’s speech recognition is investigated by using the Deep Neural Network Hidden Markov Model (DNN-HMM) hybrid and the Subspace Gaussian Mixture Model (SGMM) acoustic modeling approach. In the investigated scenario training data is limited to about 7 hours of speech from children in the age range 7-13 and testing data consists in read clean speech from child...

In most of state-of-the-art speech recognition systems, Gaussian mixture models (GMMs) are used to model the density of the emitting states in the hidden Markov models (HMMs). In a conventional system, the model parameters of each GMM are estimated directly and independently given the alignment. This results a large number of model parameters to be estimated, and consequently, a large amount of...

Bu çal??mada, 2003-2016 y?llar?n? kapsayan Türkiye dâhil 16 geli?mekte olan ülke için; ekonomik kalk?nma ve gelir da??l?m?n?n yoksulluk üzerindeki etkisi Dinamik Panel Veri tahmin yöntemlerinden Sistem Genelle?tirilmi? Momentler Metodu (SGMM) kullan?larak edilmi?tir. amaçla iki farkl? model kullan?lm??t?r. SGMM tahmincisinden elde edilen sonuçlarda, modelde de de?i?keni kendi gecikmeli de?eri i...

The goal of this study is to examine the impact remittance inflow on inflation using System Generalized Method Moments (SGMM) and Dumitrescu-Hurlin Granger causality approach in countries from Central Eastern Europe over period 1994 2019. As levels economic financial development vary considerably across these some them are member states European Union (EU), we split into two more homogenous gro...