Class-Based Contextual Modeling for Handwritten {Arabic} Text Recognition

Irfan Ahmad and Gernot A. Fink
Proc. Int. Conf. on Frontiers in Handwriting Recognition, 2016.

Shenzhen, China

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Abstract

In this paper we will present our investigations related to contextual modeling for HMM-based handwritten Arabic text recognition. We will, first, discuss the justifications and the need for contextual modeling for handwritten Arabic text recognition. Next, we will discuss the issues related to contextual modeling for Arabic text recognition. Finally, we will present our novel class-based contextual modeling for HMM-based handwritten Arabic text recognition. Experiment results on word recognition tasks show improvements in word recognition rates when compared to using standard contextual HMMs. Moreover, the recognizers are significantly more compact as compared to the standard contextual HMM systems.