Multistream Articulatory Feature-Based Models for Visual Speech Recognition
We study the problem of automatic visual speech recognition (VSR) using dynamic Bayesian network (DBN)-based models consisting of multiple sequences of hidden states, each corresponding to an articulatory feature (AF) such as lip opening (LO) or lip rounding (LR). A bank of discriminative articulato...
Main Authors: | Glass, James R., Saenko, Ekaterina, Livescu, Karen, Darrell, Trevor J. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers
2010
|
Online Access: | http://hdl.handle.net/1721.1/60293 https://orcid.org/0000-0002-3097-360X |
Similar Items
-
Articulatory features for robust visual speech recognition
by: Saenko, Ekaterina, 1976-
Published: (2005) -
Articulatory phonetic features for improved speech recognition
by: Huang, Guangpu.
Published: (2013) -
Model-based articulatory phonetic features for improved speech recognition
by: Huang, Guangpu, et al.
Published: (2013) -
Feature-based pronunciation modeling for automatic speech recognition
by: Livescu, Karen, 1975-
Published: (2008) -
Analysis and modeling of non-native speech for automatic speech recognition
by: Livescu, Karen, 1975-
Published: (2013)