Information visualization and its application to machine translation
Rebecca Hwa, University of Pittsburgh
April 12, 2011
In this talk, I will present an interactive interface that helps users to explore and understand imperfect outputs from automatic machine translation (MT) systems. The target users of our system are people who do not understand the original (source) language. Through a visualization of multiple linguistic resources, our system enables users to identify potential translation mistakes and make educated guesses as to how to correct them. Experimental results suggest that users of our prototype are able to correct some difficult translation errors that they would have found baffling otherwise. The experiments further suggest adaptive methods to improve standard phrase-based machine translation systems.
Rebecca Hwa is an Associate Professor in the Department of Computer Science at the University of Pittsburgh. Before joining Pitt, she was a postdoc at University of Maryland. She received her PhD in Computer Science from Harvard University in 2001 and her B.S. in Computer Science and Engineering from UCLA in 1993. Dr. Hwa's primary research interests include multilingual processing, machine translation, and semi-supervised learning methods. Additionally, she has collaborated with colleagues on information visualization, sentiment analysis, and bioinformatics. She is a recipient of the NSF CAREER Award. Her work has also been supported by NIH and DARPA. Dr. Hwa currently serves as the chair of the executive board of the North American Chapter of the Association for Computational Linguistics.