Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02) Minimum Classification Error Training for Online Handwritten Word Recognition Ontario, Canada August 06-August 08 ISBN: 0-7695-1692-0
We describe an application of the Minimum Classification Error (MCE) training criterion to online unconstrained-style word recognition. The described system uses allograph-HMMs to handle writer variability. The result, on vocabularies of 5k to 10k, shows that MCE training achieves around 17% word error rate reduction when compared to the baseline Maximum Likelihood system.
Citation:
Alain Biem, "Minimum Classification Error Training for Online Handwritten Word Recognition," iwfhr, pp.61, Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02), 2002 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||