A New Hybrid Approach to Large Vocabulary Cursive Handwriting Recognition

Authors:
Affiliations:
Venue:
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Year:
1998

Citing 3
Cited 2

Improved On-Line Handwriting Recognition Using Context Dependent Hidden Markov Models

ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Advanced training methods and new network topologies for hybrid MMI-Connectionist/HMM speech recognition systems

ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Off-Line Cursive Handwriting Recognition Compared with On-Line Recognition

ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472

Writer Adaptation for Online Handwriting Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-commutative Logic for Hand-Written Character Modeling

AISC '02/Calculemus '02 Proceedings of the Joint International Conferences on Artificial Intelligence, Automated Reasoning, and Symbolic Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel hybrid modeling technique that is used for the first time in Hidden Markov Model-based handwriting recognition. This new approach combines the advantages of discrete and continuous Markov models and it is shown that this is especially suitable for modeling the features typically used in handwriting recognition. The performance of this hybrid technique is demonstrated by an extensive comparison with traditional modeling techniques for a difficult large vocabulary handwriting recognition task.