Symposium on Mathematical Statistics in Natural Language, San Francisco, CA, February 2001

美国科学促进会(AAAS)将在2001年的会议上举行一次专题讨论会，主题是自然语言分析和处理的统计学方面。这次专题讨论会是由计算语言学协会的一个特别兴趣小组语言数学协会(MOL)发起的，该协会每年举行两次会议，至今已超过10年。拟议中的研讨会的更大目标是提高对自然语言结构和处理的数学研究的普遍科学意识。语言的形式和计算研究借鉴了广泛的数学领域(其中包括形式语言理论；复杂性；古典和非经典逻辑；代数和范畴理论；博弈论)，并启发了其中一些领域的创新和扩展。在美国科学促进会专题讨论会上，很难以一种既能体现其广度又能体现其深度的方式处理这项工作的全部内容。因此，专题讨论会将集中讨论一个更明确的主题--自然语言分析的统计学方面--以一种将语言工程、语言结构和处理方面的技术进步联系在一起的方式。语言的能力取决于生物天赋和经验的相互作用，这样，面对说话者之间的广泛差异，在不断变化的语境中和随着时间的推移，对物理对象的稳定解释是可能的。存储、搜索和处理的计算方法的进步使以一种易于定量的方法对天赋和经验的动态交互作用进行定性建模成为可能。本次研讨会以统计学和信息论为基础，重点探讨了解决这一系列问题的方法。介绍将首先对语音处理(这是成功和可用的计算性语音到文本处理的基础)方面基于统计的工作进行调查。然后，它将研究这些思想在句法分析和词汇歧义解决中的应用。演讲的目的将是强调不同统计方法对自然语言分析和处理中不同问题的适当性的重要性，并展示当前模型之间的区别如何与监督学习和非监督学习的区别等经典问题联系起来。

A symposium will be held at the 2001 meeting of the American Association for the Advancement of Science (AAAS) on the topic of statistical aspects of natural language analysis and processing.This symposium originates with the Association for the Mathematics of Language (MOL), a special interest group of the Association for Computational Linguistics which has held bi-annual meetings for over 10 years. The bigger goal of the proposed symposium is to heighten general scientific awareness of mathematical investigations of natural language structure and processing. Formal and computational studies of language draw on a broad range of mathematical fields (among them formal language theory; complexity; classical and non-classical logic; algebra and category theory; game theory) and have inspired innovations and extensions in a number of them. It would be difficult in a AAAS Symposium to address the full range of this work in a way that would do justice to both its breadth and its depth. The symposium will therefore concentrate on a single, more sharply delineated topic -- statistical aspects of natural language analysis -- in a way that connects technological advances in language engineering, linguistic structure and processing.Capacity for language depends on the interaction of biological endowment and empirical experience, in such a way that the stable interpretation of physical objects is possible in the face of broad variation across speakers, in changing contexts, and over time. Advances in computational methods of storage, search, and processing make it possible to model the dynamic interaction of endowment and experience qualitatively, in a way amenable to quantitative methods. This symposium focuses on approaches to this range of problems based on statistics and information theory. The presentations will begin with a survey of statistically-based work on speech processing (which underlies successful and available computational speech-to-text processing). It will then examine applications of these ideas to syntactic parsing and lexical ambiguity resolution. The presentations will be designed to stress the importance of the appropriateness of different statistical methodsto different problems in natural language analysis and processing and to show how distinctions among current models connect with such classical problems as the distinction between supervised and unsupervised learning.