Automatic lip reading in the Dutch language using active appearance models on high speed recordings

Authors:
Alin Gavril Chitu;Karin Driel;Leon J. M. Rothkrantz
Affiliations:
Delft University of Technology, Man-Machine Interaction Group, Department Mediamatica, Delft, The Netherlands;Delft University of Technology, Man-Machine Interaction Group, Department Mediamatica, Delft, The Netherlands;Delft University of Technology, Man-Machine Interaction Group, Department Mediamatica, Delft, The Netherlands
Venue:
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Year:
2010

Citing 3
Cited 0

Design and Use of Linear Models for Image Motion Analysis

International Journal of Computer Vision
Interpreting Face Images Using Active Appearance Models

FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Automatic Lipreading with Limited Training Data

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents our work on lip reading in the Dutch language. The results are based on a new data corpus recorded at 100Hz in our group. The NDUTAVSC corpus is to date the largest corpus build for lip reading in Dutch. For parameterising the input data we use Active Appearance Models. Based on the results of AAM we define a set of high level geometric features which are used for training recognizer systems for different recognition tasks, such as fixed length digits strings, random length letters strings, random word sequences, fixed topic continuous speech and random continuous speech. We show that our approach gives great improvements compared to previous results. We also investigate the influence of the high speed recordings on the performance of the recognition. We show that in the case of high speech rate the use of higher speed recordings is compulsory.