Dr. Victor ZUE 舒为都 博士
Delta Electronics Professor, Electrical Engineering and Computer Science
Massachusetts Institute of Technology
美国麻省理工学院电气工程与计算机科学系教授
http://people.csail.mit.edu/zue/

BIO:
Victor Zue is the Delta Electronics Professor of Electrical Engineering and Computer Science at M.I.T. and the Director of the Institute's Computer Science and Artificial Intelligence Laboratory (CSAIL). In the early part of his career, Victor conducted research in acoustic phonetics and phonology, codifying the acoustic manifestation of speech sounds and the phonological rules governing the realization of pronunciation in American English. Subsequently, his research interest shifted to the development of spoken language interfaces to make human-computer interactions easier and more natural. Between 1989 and 2001, he headed the Spoken Language Systems Group at the M.I.T. Laboratory for Computer Science, which has pioneered the development of many systems that enable a user to interact with computers using spoken language.

Outside of M.I.T., Victor has consulted for many multinational corporations, and he has served on many planning, advisory, and review committees for the US Department of Defense, the National Science Foundation, and the National Academies of Science and Engineering. From 1996-1998, he chaired the Information Science and Technology, or ISAT, study group for the Defense Advanced Research Projects Agency of the U.S. Department of Defense, helping the DoD formulate new directions for information technology research. In 1999, he received the DARPA Sustained Excellence Award. Victor is a Fellow of the Acoustical Society of America, and a member of the U.S. National Academy of Engineering.

Presentation Title: On Organic Interfaces

Abstract:
For over four decades, the research community has taken remarkable strides in advancing human language technologies. This has resulted in the emergence of spoken dialogue interfaces that can communicate with humans on their own terms. For the most part, however, we have assumed that these interfaces are static; it knows what it knows and doesn't know what it doesn't. In my opinion, we are not likely to succeed until we can build interfaces that behave more like organisms that can learn, grow, reconfigure, and repair themselves, much like humans. In this talk, I will argue my case and outline some new research challenges.