| Building an information retrieval test collection for spontaneous conversational speech |
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Annual ACM Conference on Research and Development in Information Retrieval
archive
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
table of contents
Sheffield, United Kingdom
SESSION: Test collections
table of contents
Pages: 41 - 48
Year of Publication: 2004
ISBN:1-58113-881-4
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Authors
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Douglas W. Oard
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University of Maryland, College Park, MD
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Dagobert Soergel
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University of Maryland, College Park, MD
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David Doermann
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University of Maryland, College Park, MD
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Xiaoli Huang
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University of Maryland, College Park, MD
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G. Craig Murray
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University of Maryland, College Park, MD
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Jianqiang Wang
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University of Maryland, College Park, MD
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Bhuvana Ramabhadran
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IBM T.J. Watson Research Center, Yorktown Heights, NY
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Martin Franz
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IBM T.J. Watson Research Center, Yorktown Heights, NY
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Samuel Gustman
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Visual History Foundation, Los Angeles, CA
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James Mayfield
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The Johns Hopkins University
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Liliya Kharevych
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California Institute of Technology
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Stephanie Strassel
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Linguistic Data Consortium
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Downloads (6 Weeks): 12, Downloads (12 Months): 65, Citation Count: 2
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ABSTRACT
Test collections model use cases in ways that facilitate evaluation of information retrieval systems. This paper describes the use of search-guided relevance assessment to create a test collection for retrieval of spontaneous conversational speech. Approximately 10,000 thematically coherent segments were manually identified in 625 hours of oral history interviews with 246 individuals. Automatic speech recognition results, manually prepared summaries, controlled vocabulary indexing, and name authority control are available for every segment. Those features were leveraged by a team of four relevance assessors to identify topically relevant segments for 28 topics developed from actual user requests. Search-guided assessment yielded sufficient inter-annotator agreement to support formative evaluation during system development. Baseline results for ranked retrieval are presented to illustrate use of the collection.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 2
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K. Y. Lin , S. H. Hsieh , H. P. Tserng , K. W. Chou , H. T. Lin , C. P. Huang , K. F. Tzeng, Enabling the creation of domain-specific reference collections to support text-based information retrieval experiments in the architecture, engineering and construction industries, Advanced Engineering Informatics, v.22 n.3, p.350-361, July, 2008
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