Collaborative Research on Knowledge Aquisition for Japanese-English Machine Translation

日英机器翻译知识获取协同研究

• 批准号: 9303013
• 负责人: Ralph Grishman
• 金额: $ 16.09万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-08-15 至 1997-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9303013&HistoricalAwards=false
• 关键词: Collaborative; Research; Knowledge; Aquisition; Japanese

9303013 Grishman This is the second year of a collaborative project between Monmouth College and New York University seeks to gather correspondences between expressions in source and target parallel corpora in Japanese and English with the objective of generalizing these correspondences to create rules for use in a translation system. The performance of translation systems has been often limited to a great extent by our ability to encode information about such correspondences manually. In this project the texts in the source and target languages are parsed and then syntactically regularized, producing regularized parse trees. A tree-matching procedure aligns the corresponding trees from the source and target texts, producing a set of detailed correspondences between source and target structures. A set of sublanguage (semantic) word classes is then defined and these correspondences are generalized to the extent possible using these word classes; the result is a set of rules for the transfer phase of a translation system. The approach uses corresponding programming language manuals written in Japanese and English.

小行星9303013 这是蒙茅斯学院和纽约大学合作项目的第二年，旨在收集日语和英语的源和目标平行语料库中的表达之间的对应关系，目的是概括这些对应关系，以创建用于翻译系统的规则。 翻译系统的性能通常在很大程度上受到我们手动编码此类对应信息的能力的限制。 在这个项目中，源语言和目标语言的文本被解析，然后进行语法正则化，生成正则化的解析树。 树匹配过程将源文本和目标文本中的对应树对齐，从而在源结构和目标结构之间产生一组详细的对应关系。 然后定义一组子语言（语义）词类，并使用这些词类将这些对应关系推广到可能的范围内;结果是一组用于翻译系统的转换阶段的规则。 该方法使用相应的编程语言手册编写的日语和英语。