U.S.-Switzerland Cooperative Research in Computational Linguistics

该奖项支持Brandeis大学的James Pustejovsky教授和一名研究生与瑞士日内瓦大学语义和认知研究所(ISSCO)的苏珊·阿姆斯特朗等人合作进行计算语言学研究。他们的研究目标是解释单词的组合方式，利用处理这一问题的不同角度，即词典学、语言学和统计学。问题是要在计算语义理论和实际系统之间建立联系，通过“基于使用”的标准直接处理建模语言的使用。Brandeis小组在词汇语义和自然语言生成方面带来了丰富的理论经验，而瑞士小组则提供了用于分析文本的计算平台和多语言环境，以及在机器翻译系统方面的经验。美国和瑞士研究团队之间的合作将通过利用瑞士参与者提供的多语言语料库分析得出的信息，引入跨语言视角。具体地说，这家瑞士集团参与了一个项目，即自动生成瑞士气象研究所制作的多语言天气预报。这一合作研究为语义选择理论奠定了经验基础。从根本上讲，它着眼于自然语言中的词义是如何被形式化地描述的，以解释单词在不同句子中的微妙使用，以及单词在新奇语境中的创造性使用。基于规则的技术和数据驱动技术的结合是自然语言处理研究的一个重要领域。在实践层面上，这项研究将有助于开发多语言生成器和增强机器翻译系统。

This award supports Professor James Pustejovsky of Brandeis University and a graduate student to collaborate in computational linguistics research with Susan Armstrong and others at the Institute of Semantic and Cognitive Studies (ISSCO) of the University of Geneva, Switzerland. The goal of their research is to account for the way in which words combine, taking advantage of the different perspectives from which this issue has been approached, namely, lexicographic, linguistic and statistical. The problem is to establish a connection between computational semantic theories and practical systems dealing directly with modeling language use through `usage-based` criteria. The Brandeis group brings substantial theoretical experience on lexical semantics and natural language generation, while the Swiss group contributes the computational platform and the multilingual environment for analyzing text, as well as experience in machine translation systems. Collaboration between the U.S. and Swiss research teams will introduce a cross- linguistic perspective by taking advantage of information derived from the analyses of multilingual corpora provided by the Swiss participants. Specifically, the Swiss group is involved in a project to produce automatic multilingual generation of the weather forecasts produced by the Swiss Institute of Meteorology. This collaborative research contributes to the empirical grounding of a theory of semantic selection. Fundamentally, it looks at how word meaning in natural language might be characterized formally, in order to account for both the subtle use of words in different sentences, and the `creative` use of words in novel contexts. The integration of rule-based technique and data driven technique is a major area of interest in natural language processing research. On a practical level, this research will contribute to the development of a multilingual generator and the enhancement of machine translation systems.