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» 2D Shape Recognition by Hidden Markov Models
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ICASSP
2010
IEEE
15 years 15 days ago
Multiple sequence alignment based bootstrapping for improved incremental word learning
We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Irene Ayllól Clemente, Martin Heckmann, Ger...
ICMCS
2007
IEEE
143views Multimedia» more  ICMCS 2007»
15 years 8 months ago
Hidden Conditional Random Fields for Meeting Segmentation
Automatic segmentation and classification of recorded meetings provides a basis towards understanding the content of a meeting. It enables effective browsing and querying in a me...
Stephan Reiter, Björn Schuller, Gerhard Rigol...
NIPS
2001
15 years 3 months ago
Speech Recognition with Missing Data using Recurrent Neural Nets
In the `missing data' approach to improving the robustness of automatic speech recognition to added noise, an initial process identifies spectraltemporal regions which are do...
S. Parveen, P. Green
ICASSP
2009
IEEE
14 years 11 months ago
VLSI for 5000-word continuous speech recognition
We have developed a VLSI chip for 5,000 word speakerindependent continuous speech recognition. This chip employs a context-dependent HMM (hidden Markov model) based speech recogni...
Young-kyu Choi, Kisun You, Jungwook Choi, Wonyong ...
CVPR
2006
IEEE
16 years 4 months ago
Robust AAM Fitting by Fusion of Images and Disparity Data
Active Appearance Models (AAMs) have been popularly used to represent the appearance and shape variations of human faces. Fitting an AAM to images recovers the face pose as well a...
Joerg Liebelt, Jing Xiao, Jie Yang