题目：Bayesian models of language acquisition or Where do the rules come from? 报告人：Prof. Mark Johnson
Department of Computing Faculty of Science Macquarie University Sydney, Australia 时间： 11月26日（星期五）09:00 – 11:00 地点： 蒙民伟楼109室
摘要 : Each human language contains an astronomically large (if not unbounded) number of different sentences. How can something so large and complex possibly be learnt? Over the past decade and a half we've figured out how to define probability distributions over grammars and the linguistic structures they generate, opening up the possibility of Bayesian models of language acquisition. Bayesian approaches are particularly attractive because they can exploit "prior" (e.g., innate) knowledge as well as statistical generalizations from the input. This opens the possibility of an empirical evaluation of the utility of various kinds of innate knowledge. Structured statistical learners have two major advantages over other approaches. This talk describes Bayesian methods for learning Context-Free Grammars and a generalization of them that we call Adaptor Grammars, and applies them to problems of morphological acquisition and word segmentation.  报告人简介: Mark Johnson is a Professor of Language Science (CORE) in the Department of Computing at Macquarie University. He was awarded a BSc (Hons) in 1979 from the University of Sydney, an MA in 1984 from the University of California, San Diego and a PhD in 1987 from Stanford University. He held a postdoctoral fellowship at MIT from 1987 until 1988, and has been a visiting researcher at the University of Stuttgart, the Xerox Research Centre in Grenoble, CSAIL at MIT and the Natural Language group at Microsoft Research. He has worked on a wide range of topics in computational linguistics, but his main research area is parsing and its applications to text and speech processing. He was President of the Association for Computational Linguistics in 2003, and was a professor from 1989 until 2009 in the Departments of Cognitive and Linguistic Sciences and Computer Science at Brown University.
|
