Events Calendar

NL Seminar- Yang Feng: "A Markov Model of Machine Translation using Non-parametric Bayesian Inference (ACL 2013)'

Speaker: Yang Feng, USC/ISI

Talk Title: "A Markov Model of Machine Translation using Non-parametric Bayesian Inference (ACL 2013)"

Series: Natural Language Seminar

Abstract: Most modern machine translation systems use phrase pairs as translation units, allowing for accurate modeling of phrase-internal translation and reordering. However phrase-based approaches are much less able to model sentence level effects between different phrase-pairs. We propose a new model to address this imbalance, based on a word-based Markov model of translation which generates target translations left-to-right. Our model encodes word and phrase level phenomena by conditioning translation decisions on previous decisions and uses a hierarchical Pitman-Yor Process prior to provide dynamic adaptive smoothing. This mechanism implicitly supports not only traditional phrase pairs, but also gapping phrases which are non-consecutive in the source.




Biography: Yang Feng is a posdoc of the natural language group in USC/ISI. She got her ph.D degree from Institute of Computing Technology, Chinese Academy of Sciences. Her research interests are in all aspects of machine translation and machine learning focusing on graphical models and Bayesian inference.

Home Page:
http://www.isi.edu/~yangfeng

Host: Yang Gao

More Info: http://nlg.isi.edu/nl-seminar/

Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

Audiences: Everyone Is Invited

Contact: Peter Zamar

Event Link: http://nlg.isi.edu/nl-seminar/