2008年清华大学信息技术研究院系列学术报告15

Biography

Dr. Fung is an Associate Professor at the Department of Electronic & Computer Engineering at The Hong Kong University of Science & Technology. She initiated and is the current Director of InterACT at HKUST, a joint research center with Carnegie Mellon University, University of Karlsruhe (TH) and Waseda University. She co-founded and is a member of the Human Language Technology Center (HLTC).

Dr. Fung's research interests are in automatic speech recognition and statistical natural language processing. She is a Committee Member of the IEEE Signal Processing Society Speech and Language Technology Committee (SLTC) and an Associate Editor of the ACM Transaction on Speech and Language Processing. She is a Senior Member of the IEEE and a Board Member of the ACL SIGDAT.

Dr. Fung received her PhD in Computer Science from Columbia University in 1997. She worked and studied at AT&T Bell Labs (1993 – 1997), BBN Systems & Technologies (1992), LIMSI, CNRS, France (1991), Kyoto University, Japan (1989 – 1991), and at Ecole Centrale Paris, France (1988). A fluent speaker of six European and Asian languages, Dr. Fung has been particularly interested in multilingual speech and natural language issues.

Dr. Fung has also co-founded and led a number of multinational companies specialized in developing and marketing speech and natural language solutions for internet and corporate customers.

Abstract

In the past decade, the performance of spoken language understanding systems, including speech recognition, dialog systems, speech summarization, as well as speech translation, has improved dramatically. This has resulted in an increasingly widespread use of speech and language technologies in a wide variety of applications. With more than 6900 languages in the world and the current trend of globalization, one of the most important challenges in spoken language technology today is the need to support multiple input and output languages, especially if applications are intended for international markets, linguistically diverse user communities, and non-native speakers. In many cases these applications have to support even multiple languages simultaneously to meet the needs of a multicultural society. Consequently, new algorithms and tools are required that support the simultaneous recognition of mixed-language input, the summarization of multilingual text and spoken docu¬ments, the generation of output in the appropriate language, or the accurate translation from one language to another. This talk surveys significant ongoing research programs as well as trends, prognoses and open research issues.