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» Recognition Model with Extension Fields
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ICML
2009
IEEE
14 years 8 months ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Thierry Artières, Trinh Minh Tri Do
ICASSP
2011
IEEE
12 years 11 months ago
Automatic speech recognition using Hidden Conditional Neural Fields
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagaw...
CVPR
2010
IEEE
14 years 8 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
IFIP
2004
Springer
14 years 23 days ago
Isolated Word Recognition for English Language Using LPC, VQ and HMM
: Speech recognition is always looked upon as a fascinating field in human computer interaction. It is one of the fundamental steps towards understanding human cognition and their ...
Mayukh Bhaowal, Kunal Chawla
ICMCS
2007
IEEE
151views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Exploring Contextual Information in a Layered Framework for Group Action Recognition
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often u...
Dong Zhang, Samy Bengio