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Subspace Gaussian Mixture Model

Known as: SGMM 
Subspace Gaussian Mixture Model (SGMM) is an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure… 
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Papers overview

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2018
2018
Adversarial perturbations are noise-like patterns that can subtly change the data, while failing an otherwise accurate classifier… 
2015
2015
The aim of this experiment was to investigate the effect of quaternarybenzophenantridine (QBA) and protopine alkaloids (PA… 
2014
2014
In computer-assisted language learning (CALL), speech data from non-native speakers are usually insufficient for acoustic… 
2014
2014
Recent advancement in deep neural network (DNN) has surpassed the conventional hidden Markov model-Gaussian mixture model (HMM… 
2014
2014
A two-stage speaker adaptation approach is proposed for the subspace Gaussian mixture model (SGMM) [1] in large vocabulary… 
2012
2012
This paper describes experimental results of applying Subspace Gaussian Mixture Models (SGMMs) in two completely diverse acoustic… 
2011
2011
In this paper we present a vectorial representation of the HMM states that is inspired by the Subspace Gaussian Mixture Models… 
2009
2009
The relationship between globalization and economic growth in the developing countries remains controversial. Liberals argue that… 
2006
2006
More than 60% of the Dutch motorways are covered with porous asphalt (PA) which has many advantages; however, its lifespan is… 
Highly Cited
2004
Highly Cited
2004
Realistic models for node movement are essential in simulating mobile ad hoc networks. Many MANET scenarios are most…