Minimum Classification Error Training for Online Handwritten Word Recognition

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	Similar Articles Articles by Alain Biem

Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)

Ontario, Canada

August 06-August 08

ISBN: 0-7695-1692-0

	ASCII Text	x
	Alain Biem, "Minimum Classification Error Training for Online Handwritten Word Recognition," Frontiers in Handwriting Recognition, International Workshop on, pp. 61, Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02), 2002.

	BibTex	x
	@article{ 10.1109/IWFHR.2002.1030885, author = {Alain Biem}, title = {Minimum Classification Error Training for Online Handwritten Word Recognition}, journal ={Frontiers in Handwriting Recognition, International Workshop on}, volume = {0}, year = {2002}, isbn = {0-7695-1692-0}, pages = {61}, doi = {http://doi.ieeecomputersociety.org/10.1109/IWFHR.2002.1030885}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Frontiers in Handwriting Recognition, International Workshop on TI - Minimum Classification Error Training for Online Handwritten Word Recognition SN - 0-7695-1692-0 SP EP A1 - Alain Biem, PY - 2002 KW - null VL - 0 JA - Frontiers in Handwriting Recognition, International Workshop on ER -

Alain Biem, IBM T. J. Watson Research Center

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IWFHR.2002.1030885

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

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