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» A Markov Random Field Model for Automatic Speech Recognition
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FLAIRS
2006
13 years 9 months ago
An Empirical Exploration of Hidden Markov Models: From Spelling Recognition to Speech Recognition
Hidden Markov models play a critical role in the modelling and problem solving of important AI tasks such as speech recognition and natural language processing. However, the stude...
Shieu-Hong Lin
NAACL
2003
13 years 9 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
CVPR
2010
IEEE
14 years 20 days ago
A Novel Markov Random Field Based Deformable Model for Face Recognition
In this paper, a new scheme to address the face recognition problem is proposed. Different from traditional face recognition approaches which represent each facial image by a sing...
Shu Liao, Albert C.S. Chung
CVPR
2009
IEEE
15 years 2 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
ICCV
2007
IEEE
14 years 2 months ago
Real-Time Automatic Kinematic Model Building for Optical Motion Capture Using a Markov Random Field
Abstract. We present a completely autonomous algorithm for the real-time creation of a moving subject’s kinematic model from optical motion capture data and with no a priori info...
Stjepan Rajko, Gang Qian