本课程包含完整的讲稿。另外，在阅读材料部分里提供了大量的推荐和指定书目。
This course features a complete set of lecture notes. In addition an extensive bibliography of assigned and recommended readings is provided in the readings section.

本课程是研究生自然语言处理的入门课程，主要涉及从计算机的观点研究人类語言。

课程内容涵盖语法、语义和篇章層次的处理。重点是基于语料库的方法和算法，例如隐马尔可夫模型（Hidden Markov Model）和概率上下文无关文法。我们將在多种应用中讨论这些方法和模型的使用，包括句法分析，信息抽取，统计机器翻译和自动摘要等。

本学科是一门人工智能及应用的综合学科。
This course is a graduate level introduction to natural language processing, the primary concern of which is the study of human language from a computational perspective.

The class will cover models at the level of syntactic, semantic and discourse processing. The emphasis will be on corpus-based methods and algorithms, such as Hidden Markov Models and probabilistic context free grammars. We will discuss the use of these methods and models in a variety of applications including syntactic parsing, information extraction, statistical machine translation, and summarization.

This subject qualifies as an Artificial Intelligence and Applications concentration subject.

技术需求

本课程网站的.gz和.tar文件需要用文件解压缩软件打开，例如Winzip®或StuffIt®。本课程网站的.ps文件可以用Postscript浏览器软件來浏览，例如 Ghostscript/Ghostview。

File decompression software, such as Winzip® or StuffIt®, is required to open the .gz and .tar files found on this course site. Postscript viewer software, such as Ghostscript/Ghostview, can be used to view the .ps files found on this course site.