US-Egypt Cooperative Research: Integrating Statistical Machine Translation from Arabic to English with Syntactic and Semantic Analysis

美国-埃及合作研究：将阿拉伯语到英语的统计机器翻译与句法和语义分析相结合

• 批准号: 0210165
• 负责人: Kevin Knight
• 金额: $ 2.5万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2004-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0210165&HistoricalAwards=false
• 关键词: US; Egypt; Cooperative; Research; Integrating

0210165KnightDescription: This award is to support a collaborative project between Dr. Kevin Knight, Information Sciences Institute (ISI), University of Southern California, Los Angeles, California and Dr. Ahmed Rafea, Computer Science Department, The American University in Cairo(AUC), Cairo, Egypt. They plan to explore a new method for automatic translation between Arabic and English. The so-called statistical machine translation method exploits both fast computers and the existence of large human-translated documents. The investigators plan to develop new models based on bilingual texts that they will manually annotate. These annotations will show how the translation process should move from Arabic into syntactic/semantic structures and from there into English. In the first stage, a substantial collection of United Nations documents translated into Arabic will be manually annotated with morphological, syntactic and semantic information by graduate students at the AUC. In the second stage, the annotated corpus will be used to train morphological analyzers and parsers of Arabic, in order to automate annotation in the second year of the project and to study the annotations of parallel Arabic and English sentences for the development of syntactic and semantic translation models. In the third and fourth stages of the proposed research, existing learning algorithms will be investigated for their suitability to integrate the developed models with statistical machine translation systems developed at ISI.Scope: Reliable automatic translation between Arabic and English may have major impact on international commerce, technology, and science, but this requires that translation quality be improved significantly. With the proposed method, computers may gather vast amounts of translation knowledge automatically from text, and apply that knowledge to translate new documents. This research will require significant expertise in computer science, Arabic and English linguistics, and statistical inference, which are available in the two collaborating groups at USC and AUC. Dr. Knight is well known for his research in the area of statistical machine translation and he will provide supervision for the research performed by graduate students at ISI and AUC. Dr. Rafea has excellent credentials in Arabic natural language processing and in conducting collaborative research with U.S. universities. The task of addressing weaknesses in current translation models will make higher translation quality possible and will make practical use of machine translation more widespread. The research will involve U.S. and Egyptian graduate students and will promote collaboration between researchers in the US and Egypt. This project is being supported under the US-Egypt Joint Fund Program, which provides grants to scientists and engineers in both countries to carry out these cooperative activities.

0210165 Knight描述：该奖项旨在支持加州洛杉矶市南加州大学信息科学研究所（ISI）Kevin Knight博士和埃及开罗美国大学（AUC）计算机科学系Ahmed Rafea博士之间的合作项目。 他们计划探索一种阿拉伯语和英语之间自动翻译的新方法。 所谓的统计机器翻译方法既利用了快速的计算机，又利用了大量人工翻译文档的存在。研究人员计划开发基于双语文本的新模型，他们将手动注释。这些注释将显示翻译过程应该如何从阿拉伯语转换到句法/语义结构，再从那里转换到英语。 在第一阶段，将由非盟委员会的研究生对翻译成阿拉伯文的大量联合国文件进行人工注释，添加词法、句法和语义信息。 在第二阶段，注释语料库将用于培训阿拉伯语的形态分析器和语法分析器，以便在项目的第二年实现注释自动化，并研究并行阿拉伯语和英语句子的注释，以开发句法和语义翻译模型。 在第三和第四阶段的拟议研究中，现有的学习算法将调查其适合集成开发的模型与统计机器翻译系统在ISI.Scope：可靠的阿拉伯语和英语之间的自动翻译可能会对国际商业，技术和科学产生重大影响，但这需要翻译质量得到显着提高。 利用所提出的方法，计算机可以从文本中自动收集大量的翻译知识，并将这些知识应用于翻译新文档。这项研究将需要计算机科学，阿拉伯语和英语语言学以及统计推断方面的重要专业知识，这些专业知识可在南加州大学和AUC的两个合作小组中获得。 Knight博士以其在统计机器翻译领域的研究而闻名，他将为ISI和AUC的研究生进行的研究提供指导。 Rafea博士在阿拉伯语自然语言处理以及与美国大学进行合作研究方面拥有出色的资历。解决当前翻译模型中的弱点的任务将使更高的翻译质量成为可能，并将使机器翻译的实际应用更加广泛。 这项研究将涉及美国和埃及的研究生，并将促进美国和埃及研究人员之间的合作。 该项目得到了美国-埃及联合基金方案的支持，该方案向两国的科学家和工程师提供赠款，以开展这些合作活动。