Duration Models for Arabic Text Recognition Using Hidden Markov Models

Authors:
Fouad Slimane;Rolf Ingold;Adel M. Alimi;Jean Hennebert
Affiliations:
-;-;-;-
Venue:
CIMCA '08 Proceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation
Year:
2008

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Abstract

We present in this paper a system for recognition ofprinted Arabic text based on Hidden Markov Models(HMM). While HMMs have been successfully used inthe past for such a task, we report here on significantimprovements of the recognition performance with theintroduction of minimum and maximum durationmodels. The improvements allow us to build a systemworking in open vocabulary mode, i.e., without anylimitations on the size of the vocabulary. Theevaluation of our system is performed using HTK(Hidden Markov Model Toolkit) on a database of wordimages that are synthetically generated.