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Talk. Dan Jurafsky. Extracting many kinds of meaning from text and speech. (2011/09/13)

Speaker: Professor  Dan Jurafsky (Stanford University).
Date: September 13, 2011
Time: 16:00
Where
: Computer Science Faculty

Title: Extracting many kinds of meaning from text and speech.
Abstract:
Understanding natural language, while one of the oldest goals of artificial intelligence, is immensely difficult because language expresses so many kinds of meanings, embedded as it is in the rich social world of humans. In this talk I discuss work in our lab on extracting three kinds of meaning that link to the human world. We show how to learn world knowledge about events and their participants, `narrative schemes’ about how the world works, in a purely unsupervised way from large bodies of text. We show a new algorithm for the task of ‘coreference’: deciding when two mentions in a text refer to the same person or organization. Finally, we show how to automatically detect human interpersonal stances from speech and text cues in spoken conversation, detecting whether a speaker is friendly, awkward, or flirtatious. This talk describes joint work with Nate Chambers, Angel Chang, Heeyoung Lee, Chris Manning, Dan McFarland, Yves Peirsman, Karthik Raghunathan, Rajesh Ranganath, and Mihai Surdeanu.
BIO:
 Dan Jurafsky is Professor of Linguistics and Professor by Courtesy of Computer Science at Stanford University. Dan received a B.A in Linguistics in 1983 and a Ph.D. in Computer Science in 1992, both from the University of California at Berkeley, and also taught at the University of Colorado, Boulder. His research focuses on natural language understanding as well as the application of natural language processing to the behavioral and social sciences. Other research interests include the linguistics of Chinese and the linguistics of food. He is the recipient of a MacArthur Fellowship, and is the co-author with Jim Martin of the widely-used textbook “Speech and Language Processing“. It was the first book that included deep descriptions of both text and speech technology. Teachers and students of Language Technology, we know very well this nice book.

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