Alex Hauptmann

Alexander G. Hauptmann is an American Systems Scientist in the School of Computer Science at Carnegie Mellon University. He has been the leader of the Informedia Digital Library which has made seminal strides in multimedia information retrieval and won best paper awards at major conferences. He was also a founder of the international advisory committee for TRECVID.

Biography

Alex Hauptmann started at the Johns Hopkins University in 1978 and received a BA and a MA in Psychology in 1982. For two years he studied Computer Science eat the Technische Universitaet Berlin. In 1991 he received a PhD in Computer Science from the Carnegie Mellon University.

From 1984 he was researcher at the Carnegie Mellon University in the CMU speech group. The next two years he was a research associate at the School of Computer Science, since 1994 a System Scientist and since 1998 a Senior System Scientist.

In 2003 he received the Allen Newell Award for Research Excellence, for the Informedia Digital Library,with H. Wactlar, M. Christel, T. Kanade and S. Stevens.

Work

His research interests are in speech recognition, speech synthesis, speech interfaces and language in general. [ [http://www.cs.cmu.edu/afs/cs.cmu.edu/user/alex/www/HomePage.html Alexander G. Hauptmann] Carnegie Mellon University.] Over the years his research interests have led him to pursue and combine several different areas of research: man-machine communication, natural language processing and speech understanding. Alex Hauptmann. [http://www-2.cs.cmu.edu/afs/cs/user/alex/www/vita-long.pdf Biography 2008] . Retrieved 7 June 2008]

In the area of man-machine communication, he is interested in the tradeoffs between different modalities,including gestures and speech, and in the intuitiveness of interaction protocols. In natural languageprocessing, his desire is to break through the bottlenecks that are currently preventing larger scale naturallanguage applications. The latter theme was also the focus of my thesis, which investigated the use ofmachine learning on large text samples to acquire the knowledge needed for semantic natural languageunderstanding.

The approach developed in his thesis research was quite successful at using example sentences and target meanings to learn rules for semantic interpretation from syntactic structures. In the field of speech understanding, he is intrigued by the potential of combining natural language technology with clever interfaces in speech recognition applications.

References

External links

* [http://www.cs.cmu.edu/afs/cs.cmu.edu/user/alex/www/HomePage.html Home page]
* [http://www.informedia.cs.cmu.edu/ Informedia Project]