阿拉伯语翻译并行合成数据集
Noora Al-Shameri1, Hend Al-Khalifa1
1Information Technology Department, King Saud University, Riyadh, Saudi Arabia.
Data in brief
|November 5, 2024
概括
这项研究介绍了一个新的阿拉伯语翻译的并行数据集,使用逆向翻译创建. 本资源旨在改善自然语言处理 (NLP) 任务和阿拉伯语言理解.
科学领域:
- 自然语言处理 (NLP) 是一种自然语言处理.
- 计算语言学 计算语言学
- 数据科学数据科学数据科学
背景情况:
- 自然语言处理 (NLP) 应用程序需要强大的阿拉伯语数据集.
- 现有的阿拉伯语数据集缺乏足够的并行数据.
- 数据增强对于扩大语言资源至关重要.
研究的目的:
- 开发一个全面的阿拉伯语翻译的平行数据集.
- 为了解决阿拉伯语对译文生成资源的短缺问题.
- 通过改进数据来增强各种NLP任务.
主要方法:
- 来自各种阿拉伯语来源的句子集合.
- 使用反向翻译技术进行数据增强.
- 产生的数据集的预处理和严格评估.
主要成果:
- 创建了一个可靠和有用的阿拉伯语翻译的并行数据集.
- 该数据集有效地解决了阿拉伯语转述生成研究中的差距.
- 该数据集适用于各种NLP应用.
结论:
- 开发的数据集对于推进阿拉伯语NLP至关重要.
- 它支持机器翻译,文本总结和情感分析.
- 该资源促进了阿拉伯语言处理和相关领域的创新.
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