历史文献中OCR后编的辅助工具
A Tool for Facilitating OCR Postediting in Historical Documents
摘要：
历史文件的光学字符识别（OCR）是一个复杂的程序，存在一系列独特的实质性问题，包括字体不一致和扫描质量低。因此，即使是最复杂的OCR引擎也会产生错误。本文报告了一个工具，用于对Tesseract的输出进行后期编辑，更具体地说，用于纠正数字化历史文档中的常见错误。拟议的工具建议替代词的形式没有发现在指定的词汇。假设的错误在后编辑中基于语言模型（LM）的分数被假定正确的替代替换。该工具是测试的一章书的论文对规范贸易和雇用穷人的这个王国（卡里，1719年）。如下所示，该工具成功地纠正了一些常见错误。虽然有时不可靠，但它也是透明的，并受到人为干预。
英文摘要：
Optical character recognition (OCR) for historical documents is a complex procedure subject to a unique set of material issues, including inconsistencies in typefaces and low quality scanning. Consequently, even the most sophisticated OCR engines produce errors. This paper reports on a tool built for postediting the output of Tesseract, more specifically for correcting common errors in digitized historical documents. The proposed tool suggests alternatives for word forms not found in a specified vocabulary. The assumed error is replaced by a presumably correct alternative in the post-edition based on the scores of a Language Model (LM). The tool is tested on a chapter of the book An Essay Towards Regulating the Trade and Employing the Poor of this Kingdom (Cary ,1719). As demonstrated below, the tool is successful in correcting a number of common errors. If sometimes unreliable, it is also transparent and subject to human intervention.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
