2008年清华大学信息技术研究院系列学术报告17

Biography

Chin-Hui Lee is a professor at School of Electrical and Computer Engineering, Georgia Institute of Technology. Dr. Lee received the B.S. degree in Electrical Engineering from National Taiwan University, Taipei, in 1973, the M.S. degree in Engineering and Applied Science from Yale University, New Haven, in 1977, and the Ph.D. degree in Electrical Engineering with a minor in Statistics from University of Washington, Seattle, in 1981.

Dr. Lee started his professional career at Verbex Corporation, Bedford, MA, and was involved in research on connected word recognition. In 1984, he became affiliated with Digital Sound Corporation, Santa Barbara, where he engaged in research and product development in speech coding, speech synthesis, speech recognition and signal processing for the development of the DSC-2000 Voice Server. Between 1986 and 2001, he was with Bell Laboratories, Murray Hill, New Jersey, where he became a Distinguished Member of Technical Staff and Director of the Dialogue Systems Research Department. His research interests include multimedia communication, multimedia signal and information processing, speech and speaker recognition, speech and language modeling, spoken dialogue processing, adaptive and discriminative learning, biometric authentication, and information retrieval. From August 2001 to August 2002 he was a visiting professor at School of Computing, The National University of Singapore. In September 2002, he joined the Faculty Georgia Institute of Technology.

Prof. Lee has participated actively in professional societies. He is a member of the IEEE Signal Processing Society (SPS), Communication Society, and the International Speech Communication Association (ISCA). In 1991-1995, he was an associate editor for the IEEE Transactions on Signal Processing and Transactions on Speech and Audio Processing. During the same period, he served as a member of the ARPA Spoken Language Coordination Committee. In 1995-1998 he was a member of the Speech Processing Technical Committee and later became the chairman from 1997 to 1998. In 1996, he helped promote the SPS Multimedia Signal Processing Technical Committee in which he is a founding member.

Dr. Lee is a Fellow of the IEEE, and has published more than 250 papers and 25 patents on the subject of automatic speech and speaker recognition. He received the SPS Senior Award in 1994 and the SPS Best Paper Award in 1997 and 1999, respectively. In 1997, he was awarded the prestigious Bell Labs President's Gold Award for his contributions to the Lucent Speech Processing Solutions product. Dr. Lee often gives seminal lectures to a wide international audience. In 2000, he was named one of the six Distinguished Lecturers by the IEEE Signal Processing Society. He was also named one of the two ISCA's inaugural Distinguished Lecturers in 2007-2008. Recently he won the SPS's 2006 Technical Achievement Award for "Exceptional Contributions to the Field of Automatic Speech Recognition".

Abstract

Many of the recent advances in statistical natural language processing (NLP) are mainly attributed to a number of key factors, namely: (1) Shannon’s source-channel characterization of NLP problems; (2) the availability of large collections of labelled text data; (3) the implementation of efficient and effective machine learning algorithms; and (4) increase in computing power to learn statistical properties in data and real-time execution of may real-world NLP applications. This same data-driven, pattern matching paradigm prevails in the field of automatic speech recognition (ASR). We review the fundamentals in ASR and extend the same paradigm to some popular NLP tasks, such as N-gram language modelling, part of speech tagging, text understanding, statistical parsing, text categorization, and machine translation. The learning curve in ASR development in the last thirty years gives up plenty of lessons to predict what’s laying ahead of us in research and applications in statistical NLP.