Time: 2pm-3pm, Friday, October 23 Place: Room 4422, CUNY Graduate Center, 365 Fifth Ave (34str&35str). Speaker: Fei Huang (IBM T.J. Watson Research Center) Title: Confidence Measure for Word Alignment Abstract: Data-driven machine translation learn various models from large amount of bilingual data with word alignment. "Noises" in the training data often introduce many word alignment errors. We present a confidence measure for word alignment based on the posterior probability of alignment links. We introduce sentence alignment confidence measure and alignment link confidence measure. Based on these measures, we improve the alignment quality by selecting high confidence sentence alignments and alignment links from multiple word alignments of the same sentence pair. Additionally, we remove low confidence alignment links from the MaxEnt word alignment of a bilingual training corpus, which increases the alignment F-score, improves Chinese-English and Arabic-English translation quality and significantly reduces the phrase translation table size. Bio: Dr. Fei Huang is a research staff member at IBM T.J. Watson Research Center, His current research focus on statistical machine translation while his interest is on various aspects of statistical NLP. He obtained his PhD. from School of Computer Science at Carnegie Mellon University in 2006, where he worked on information extraction and machine translation, specializing in named entity extraction and translation from text and speech.