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JCE-TC Japanese-Chinese-English Translation Corpus and Its Application

JCE-TC日汉英翻译语料库及其应用

基本信息

批准号：
09044179
负责人：
REN Fuji
金额：
$ 5.95万
依托单位：
Hiroshima City University
依托单位国家：
日本
项目类别：
Grant-in-Aid for international Scientific Research
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 1998
项目状态：
已结题

项目摘要

In this project, We studied Japanese-Chinese-English Translation Corpus and Its Application.(l)We have proposed an algorithm for automatically aligning Chinese and Japanese parallel Corpora. The algorithm initially attempts to align the Chinese and Japanese sentences using measurements of the differences between sentence lengths in the two documents.(2)We have proposed a new concept called "Sensitive Word", and described the segmentation problem and the impact of the sensitive word on natural language processing. We have shown the result of our examination.(3)A crucial problem in rule-based machine translation is the acquisition of translation knowledge. Many studies have been conducted for automatic acquisition in the past, but they require a great deal of annotated examples. In this project, we have developed a semi-automatic mechanism to support knowledge acquisition from translation examples in Japanese-Chinese environment.(4) We have proposed a relaxed segmentation process for Chinese which extracts not noly the longest words as one usually does, but also all the short words implied. Special rules are also designed in order to recongnize and standardize sepcial words such as proper names and nominal pre-determiners. It is shown that IR based on this segmentation leads to a higher effectiveness than bigrams.(5) We have taken a new hybrid multi-engine approach to machine translation, which can take the advantages of the previously proposed methods and get rid of their disadvantages.(6) We will publisize our "Translation corpora" and "Chinese dictionary" on the Web after we improve the multi-lingual envionment.

本课题研究日汉英翻译语料库及其应用。(l)We提出了一种中日平行语料库的自动对齐算法。该算法首先尝试使用两个文档中句子长度之间的差异的测量来对齐中文和日文句子。(2)We提出了“敏感词”的概念，并阐述了敏感词的切分问题及其对自然语言处理的影响。我们已经出示了检查结果。(3)A基于规则的机器翻译的关键问题是翻译知识的获取。在过去，许多研究已经进行了自动获取，但他们需要大量的注释的例子。在这个项目中，我们已经开发了一个半自动的机制，以支持知识获取的翻译实例在日本-中国的环境。(4)我们提出了一个宽松的分割过程中，提取不仅是最长的词，因为一个通常，但也包括所有的短词隐含。为了识别和规范专有名词、名词性预限定词等特殊词语，还设计了特殊规则。结果表明，基于这种分割的IR导致比二元组更高的有效性。(5)我们采用了一种新的混合多引擎方法来进行机器翻译，它可以利用以前提出的方法的优点，并摆脱它们的缺点。(6)我们将在完善多语种环境后，在网上扩大我们的“翻译语料库”和“汉语词典”。