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ICASSP
2010
IEEE
13 years 8 months ago
A novel estimation of feature-space MLLR for full-covariance models
In this paper we present a novel approach for estimating featurespace maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maxim...
Arnab Ghoshal, Daniel Povey, Mohit Agarwal, Pinar ...
CVPR
2009
IEEE
14 years 2 months ago
On bias correction for geometric parameter estimation in computer vision
Maximum likelihood (ML) estimation is widely used in many computer vision problems involving the estimation of geometric parameters, from conic fitting to bundle adjustment for s...
Takayuki Okatani, Koichiro Deguchi
TASLP
2002
96views more  TASLP 2002»
13 years 7 months ago
MAP speaker adaptation of state duration distributions for speech recognition
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, ...
Néstor Becerra Yoma, Jorge Silva Sán...
WCE
2007
13 years 8 months ago
Procedures of Parameters' estimation of AR(1) models into lineal state-space models
—The objective of this paper is to study how algorithms of optimization affect the parametersestimation of Autoregressive AR(1)Models. In our research we have represented the AR...
Rouhia Noomene
ECML
2005
Springer
14 years 1 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...