Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision

Natural Language Understanding: Word Spaces, Meaning, Structure, Psychological Reality, Grammaticality

Christopher Manning
Computer Science Department
Stanford University

Wednesday, February 16, 2000
refreshments 4:05PM, talk begins 4:15PM
TCseq201, Lecture Hall B


In recent years, statistical techniques based on collecting data from large language corpora have transformed natural language processing -- just as many other areas of AI -- and statistical systems are yielding better and still improving levels of task performance. In this talk I will pick out and examine some of what can be done so successfully with statistical models, from the treatment of words to sentence parsing, but equally try to connect this work to issues of meaning, representation, psycholinguistic plausibility, grammaticality, and progress in achieving artificial intelligence.

About the Speaker

Christopher Manning is an Assistant Professor of Computer Science and Linguistics at Stanford University. His research interests include probabilistic models of language and statistical natural language processing, constraint-based theories of grammar (HPSG and LFG), computational lexicography, and syntactic typology. He received his Ph.D. in linguistics from Stanford University in 1995. From 1994-1996, he was on the faculty of the Computational Linguistics Program at Carnegie Mellon University, and from 1996-1999 he was "back home" at the University of Sydney, before returning to Stanford at the start of this academic year. His most recent book is Foundations of Statistical Natural Language Processing (MIT Press, 1999, with Hinrich Schuetze).
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Last modified: Fri Jan 7 11:23:04 PST 2000