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Printed Urdu Base Model Trained on the OpenITI Corpus

Authors: Benjamin Kiessling;

Printed Urdu Base Model Trained on the OpenITI Corpus

Abstract

Printed Urdu Base Model Trained on the OpenITI Corpus This is a text recognition model trained on the OpenITI dataset of printed Arabic-script text available here in its state of 2022-09-03. It encompasses Urdu (~11k lines) material in a variety of typefaces. The model has been obtained by fine-tuning the Arabic-script base model on the purely Urdu subset of the corpus. The ground truth was lightly normalized to NFD but is otherwise untouched. Architecture The default model architecture and hyperparameters of kraken 4.x where used. Uses The model is trained on a variety of highly diverse typefaces it is mostly intended as a base model for fine-tuning more specific models from it. In line with this it has not been extensively verified or optimized. How to Get Started with the Model Follow the instructions on installing and using kraken from the website. Metrics CER: 4.13%

Keywords

automatic-text-recognition, kraken_pytorch

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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