Publication statistics

Pub. period:1995-1999
Pub. count:4
Number of co-authors:4


Number of publications with 3 favourite co-authors:

Vibhu O. Mittal:
Stephen Reed:
Alexander I. Rudnicky:



Productive colleagues

Michael J. Witbrock's 3 most productive colleagues in number of publications:

Alexander G. Haupt..:43
Alexander I. Rudni..:17
Vibhu O. Mittal:9

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Michael J. Witbrock


Publications by Michael J. Witbrock (bibliography)

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Witbrock, Michael J. and Mittal, Vibhu O. (1999): Ultra-Summarization: A Statistical Approach to Generating Highly Condensed Non-Extractive Summaries. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1999. pp. 315-316. Available online

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Witbrock, Michael J. and Hauptmann, Alexander G. (1998): Speech Recognition for a Digital Video Library. In JASIST - Journal of the American Society for Information Science and Technology, 49 (7) pp. 619-632.

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Witbrock, Michael J. and Hauptmann, Alexander G. (1997): Using Words and Phonetic Strings for Efficient Information Retrieval from Imperfectly Transcribed Spoken Documents. In: DL97: Proceedings of the 2nd ACM International Conference on Digital Libraries 1997. pp. 30-35. Available online

Searching for relevant material in documents containing transcription errors presents new challenges for Information Retrieval. This paper examines information retrieval effectiveness on a corpus of spoken broadcast news documents. For documents transcribed using speech recognition, a substantial number of retrieval errors are due to query terms that occur in the spoken document, but are not transcribed because they are not within the speech recognition system's lexicon, even if that lexicon contains twenty thousand words. It has been shown that a phonetic lattice search in conjunction with full word search regains some of the information lost due to out-of-vocabulary words. In this paper an efficient alternative to this search is proposed that does not require a complete search of the phoneme lattices for all documents at run-time. By using fixed length strings of phonemes instead of phonetic lattices, an information retrieval system can search the phoneme space of a spoken document just as efficiently as a normal word document collection. Experimental evidence is presented that this technique permits the system to recapture some of the information lost due to out-of-vocabulary words in the speech recognition transcripts.

© All rights reserved Witbrock and Hauptmann and/or ACM Press

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Hauptmann, Alexander G., Witbrock, Michael J., Rudnicky, Alexander I. and Reed, Stephen (1995): Speech for Multimedia Information Retrieval. In: Robertson, George G. (ed.) Proceedings of the 8th annual ACM symposium on User interface and software technology November 15 - 17, 1995, Pittsburgh, Pennsylvania, United States. pp. 79-80. Available online

We describe the Informedia News-on-Demand system. News-on-Demand is an innovative example of indexing and searching broadcast video and audio material by text content. The fully-automatic system monitors TV news and allows selective retrieval to news items based on spoken queries. The user then plays the appropriate video "paragraph". The system runs on a Pentium PC using MPEG-I video compression and the Sphinx-II continuous speech recognition system [6].

© All rights reserved Hauptmann et al. and/or ACM Press

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