Lecture in Pattern Recognition

题目(TITLE)：Hierarchical Alignment

讲座人(SPEAKER)：Dr. Nianwen Xue, Computer Science Department and the Language & Linguistics Program at Brandeis University, USA

主持人(CHAIR)：Prof. Chengqing Zong

时 间(TIME)： August 12(Monday), 2013, 10:15AM

地点(VENUE)：No.1 Conference Room (3rd floor), Intelligence Building

报告摘要（ABSTRACT）：

Existing word alignment standards often attempt to align everything at the level of words. This leads to complicated alignments and spurious ambiguity in some cases and severs key dependencies in others. In this talk I will describe a project where we attempt to migrate some of the alignments to phrases, thereby simplifying word-level alignments. This alignment is based on parallel treebanks and I show that this representation can support the extraction of Hiero-style rules and tree-to-tree MT models.

报告人简介（BIOGRAPHY）：

Nianwen Xue is an Assistant Professor in the Computer Science Department and the Language & Linguistics Program at Brandeis University. Before joining Brandeis, Nianwen Xue was a research assistant professor in the Department of Linguistics and the Center for Computational Language and Education Research (CLEAR) at the University of Colorado at Boulder. Prior to that, he was a postdoctoral fellow in the Institute for Research in Cognitive Science and the Department of Computer and Information Science at the University of Pennsylvania. He got his PhD in linguistics from University of Delaware.

Nianwen Xue has broad interests in computational linguistics and natural language processing. He has devoted substantial efforts to developing linguistic corpora annotated with syntactic, semantic, temporal and discourse information that are crucial resources in the field of natural language processing. The other thread of his research involves using statistical and machine learning techniques in solving natural language processing problems. He has published work in the areas of Chinese word segmentation, syntactic and semantic parsing, coreference, discourse analysis, machine translation as well as biomedical natural language processing. His research has received support from the National Science Foundation (NSF), IARPA and DARPA. He serves on the editorial boards of ACM Transactions on Asian Language Information Processing, Language Resources and Evaluation, and Computer Processing of Oriental Languages.