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IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Boosted Audio-Visual HMM for Speech Reading
Nice, France
October 17-October 17
ISBN: 0-7695-2010-3
ASCII Text
x 
 
Pei Yin, Irfan Essa, James M. Rehg, "Boosted Audio-Visual HMM for Speech Reading," Analysis and Modeling of Faces and Gestures, IEEE International Workshop on, pp. 68, IEEE International Workshop on Analysis and Modeling of Faces and Gestures, 2003.
 
 
BibTex
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@article{ 10.1109/AMFG.2003.1240826,
author = {Pei Yin and Irfan Essa and James M. Rehg},
title = {Boosted Audio-Visual HMM for Speech Reading},
journal ={Analysis and Modeling of Faces and Gestures, IEEE International Workshop on},
volume = {0},
year = {2003},
isbn = {0-7695-2010-3},
pages = {68},
doi = {http://doi.ieeecomputersociety.org/10.1109/AMFG.2003.1240826},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Analysis and Modeling of Faces and Gestures, IEEE International Workshop on
TI - Boosted Audio-Visual HMM for Speech Reading
SN - 0-7695-2010-3
SP
EP
A1 - Pei Yin,
A1 - Irfan Essa,
A1 - James M. Rehg,
PY - 2003
KW - null
VL - 0
JA - Analysis and Modeling of Faces and Gestures, IEEE International Workshop on
ER -
 
Pei Yin, Georgia Institute of Technology
Irfan Essa, Georgia Institute of Technology
James M. Rehg, Georgia Institute of Technology
We propose a new approach for combining acoustic and visual measurements to aid in recognizing lip shapes of a person speaking. Our method relies on computing the maximum likelihoods of (a) HMM used to model phonemes from the acoustic signal, and (b) HMM used to model visual features motions from video. One significant addition in this work is the dynamic analysis with features selected by Ad-aBoost, on the basis of their discriminant ability. This form of integration, leading to boosted HMM, permits AdaBoost to find the best features first, and then uses HMM to exploit dynamic information inherent in the signal.
Citation:
Pei Yin, Irfan Essa, James M. Rehg, "Boosted Audio-Visual HMM for Speech Reading," amfg, pp.68, IEEE International Workshop on Analysis and Modeling of Faces and Gestures, 2003
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