向多语言词典的资源:一个MT辅助和人-in-the-loop多语言并行语料库与多词表达式注释
Lifeng Han1,2,3, Najet Hadj Mohamed4, Malak Rassem5
1University of Manchester, Manchester, M13 9PL UK.
概括
本研究介绍了AlphaMWE,这是一个用于机器翻译 (MT) 研究的多语言集体,专注于多词表达式 (MWE). 该集体强调了MWE翻译的挑战,并对MT错误进行了分类,有助于未来的MT系统开发.
科学领域:
- 计算语言学 计算语言学
- 自然语言处理自然语言处理.
- 机器翻译 机器翻译
背景情况:
- 多词表达式 (MWEs) 对机器翻译 (MT) 系统构成重大挑战.
- 现有的并行体通常缺乏详细的MWE注释,阻碍了专门的MT研究.
研究的目的:
- 构建一个高质量的,多语言并行语料库 (AlphaMWE),用口头MWE (vMWE) 进行注释.
- 分析最先进的MT系统对MWE翻译的性能,并对遇到的错误进行分类.
- 为推进MT研究提供有价值的资源,特别是在MWE翻译和跨语言应用方面.
主要方法:
- 使用MT辅助的人在循环注释创建一个多语言并行语料库.
- 用阿拉伯语,中文,英语,德语,意大利语和波兰语进行MWE的手动后编辑和注释.
- 严格的质量控制,包括对MT输出和注释的双重手动审查.
主要成果:
- AlphaMWE库已成功构建,具有跨六种语言手动对齐的vMWE.
- 分析显示,正确的MWE翻译仍然是当前MT系统面临的挑战,正如HOPE指标所示.
- 开发了一个特定于MWE翻译的MT错误类型的分类.
结论:
- 阿尔法MWE数据集是单语言和跨语言研究的宝贵资源,包括MWE词典,MT和信息提取.
- 这些发现强调了需要改进的MT模型,能够处理像MWE这样的复杂语言现象.
- 分类的错误类型为开发更强大的MT系统提供了具体的见解.
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