科普特字体的光学字符识别:学术版的多源方法

Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage Pub Date : 2019-05-08 DOI:10.1145/3322905.3322931

E. Lincke, Kirill Bulert, Marco Büchler

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引用次数: 0

摘要

在本文中，我们展示了OCR引擎Ocropy可以训练用于相当复杂和变化的科普特排版的字体。对于本文中提出的三种字体中的每一种，我们都使用了许多来自不同语言学和编辑标准的学术版本的文本，以及来自两种不同的科普特方言(波海里克语和萨希迪语)的文本。尽管训练数据很复杂，但我们观察到准确率达到97.5%，一种字体甚至达到99%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optical Character Recognition for Coptic fonts: A multi-source approach for scholarly editions

In this paper, we show that the OCR engine Ocropy can be trained for fonts used in rather complex and varied Coptic typeset. For each of the three fonts presented in this paper, we used a number of texts from scholarly editions with different philological and editorial standards and texts from two different dialects of Coptic (Bohairic and Sahidic). Despite the complexity of the training data, we observed accuracy rates of 97.5%, for one font even up to 99%.

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Proceedings of the 3rd International Conference on Digital Access to Textual Cultural Heritage

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