题    目（TITLE）：Bayesian models of language acquisition or Where do the rules come from?

讲 座 人（SPEAKER）: Prof. Mark Johnson；Macquarie University

主 持 人 (CHAIR)： Prof. Chengqing Zong

时    间 (TIME)： 10:00AM, December 2 (Thursday)

地    点 (VENUE)： 1115 Meeting Room

报告摘要（ABSTRACT）：

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.  First, because the generalizations they learn and the prior knowledge they utilize are both expressed in terms of explicit linguistic representations, it is clear what is learnt and what information is exploited during learning.  Second, because of the "curse of dimensionality", learners that identify and exploit structural properties of their input seem to be the only ones that have a chance of "scaling up" to learn real languages.  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（BIOGRAPHY）：

Mark Johnson is a Professor of Language Science (CORE) in the Department of Computing at Macquarie University in Sydney, Australia. 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, and more recently on Bayesian methods for grammatical inference. 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.