摩洛哥官方文件的多语言字符识别数据集
Ali Benaissa1,2, Abdelkhalak Bahri1, Ahmad El Allaoui3
1Data Science and Competitive Intelligence Team (DSCI), ENSAH, Abdelmalek Essaadi University (UAE), Tetouan, Morocco.
Data in brief
|January 8, 2024
概括
创建了一个用于多语言字符识别的新数据集,其中包括阿拉伯语,法语和塔马齐特文字. 该资源有助于将摩洛哥文件数字化,并开发先进的识别模型.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 多语言字符识别对于数字化各种文档至关重要.
- 现有的数据集可能无法充分覆盖摩洛哥官方文件中发现的特定语言和脚本变异.
- 字符识别方面的进步需要大规模的注释数据集.
研究的目的:
- 为摩洛哥官方文件量身定制的多语言字符识别构建一个全面的数据集.
- 支持文化遗产和档案材料的数字化.
- 促进开发强大的自动化文本识别系统.
主要方法:
- 使用Python脚本构建编程数据集.
- 包括各种字符集:阿拉伯语,法语,Tamazight (Tifinagh),数字,符号和特殊字符.
- 从代表性字体生成多个字符图像变体,以增强数据多样性.
主要成果:
- 一个包含大写 (26类),小写 (26类),数字 (9类),阿拉伯语 (28类),Tifinagh字母 (33类),符号 (14类) 和法国特殊字符 (16类) 的子数据集的数据集.
- 编程生成的数据确保了培训认可模型的多样性和适用性.
- 一个基础资源,用于提高跨多个脚本的字符识别准确性.
结论:
- 开发的数据集对于推进多语言字符识别至关重要,特别是对于摩洛哥语境.
- 它使历史和官方文件的数字化更有效.
- 为更广泛的模式识别和人工智能应用领域做出贡献.
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