Abstract
Electronically available multi-modal data (primarily text and meta-data) is unprecedented in terms of its volume, variety, velocity, (and veracity). The increased interest and investment in cognitive computing for building systems and solutions that enable and support richer human-machine interactions presents a unique opportunity for novel statistical models for natural language processing.
In this talk, I will give brief overview of work at IBM in developing novel statistical models for NLP such as statistical parsing, question-answering systems, and machine translation. I will also discuss the significant progress in the quality of statistical machine translation over the past few years with techniques that include the use of source language analysis including parse forests of the input, techniques for cross-system adaptation, and improved data modeling for informal communications such as found in blogs. I will also give an update on techniques to improve the value of machine translation for human translators for MT Post Editing. In particular, I will discuss the impact of MT on human translator productivity in translating English to Japanese, a notoriously challenging language pair.
Biography
Salim Roukos is Senior Manager of Multi-Lingual NLP and CTO for Translation Technologies at IBM T. J. Watson Research Center. Dr. Roukos received his B.E. from the American University of Beirut, in 1976, his M.Sc. and Ph.D. from the University of Florida, in 1978 and 1980, respectively. He joined Bolt Beranek and Newman from 1980 through 1989, where he was a Senior Scientist in charge of projects in speech compression, time scale modification, speaker identification, word spotting, and spoken language understanding. He was an Adjunct Professor at Boston University in 1988 before joining IBM in 1989. Dr. Roukos has served as Chair of the IEEE Digital Signal Processing Committee in 1988.
Salim Roukos currently leads a group at IBM T.J. Watson research Center that focuses on various problems using machine learning techniques for natural language processing. The group pioneered many of the statistical methods for NLP from statistical parsing, to natural language understanding, to statistical machine translation and machine translation evaluation metrics (BLEU metric). Roukos has over a 150 publications in the speech and language areas and over two dozen patents. Roukos was the lead of the group which introduced the first commercial statistical language understanding system for conversational telephony systems (IBM ViaVoice Telephony) in 2000 and the first statistical machine translation product for Arabic-English translation in 2003. He has recently lead the effort to create IBM’s offering of IBM Real-Time Translation Services (RTTS) a platform for enabling real-time translation applications such as multilingual chat and on-demand document translation.