An Overview of the AT&T Spoken Document Retrieval System

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameProceedings of DARPA Broadcast News Transcription and Understanding Workshopen_US
dc.contributor.authorChoi, Johnen_US
dc.contributor.authorHindle, Donen_US
dc.contributor.authorHirschberg, Juliaen_US
dc.contributor.authorMagrin-Chagnolleau, Ivanen_US
dc.contributor.authorNakatani, Christineen_US
dc.contributor.authorPereira, Fernandoen_US
dc.contributor.authorSinghal, Amiten_US
dc.contributor.authorWhittaker, Steveen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:52:16Z
dc.date.available2007-10-31T00:52:16Z
dc.date.issued1998-01-15en
dc.date.modified2004-11-10en_US
dc.date.note2004-01-14en_US
dc.date.submitted1998-01-15en_US
dc.descriptionConference Paperen_US
dc.description.abstractWe present an overview of a spoken document retrieval system developed at AT&T Labs-Research for the HUB4 Broadcast News corpus. This overview includes a description of the intonational phrase boundary detection, classification, speech recognition, information retrieval and user interface components of the system, along with updated system assessments based on the 49-query task defined for the TREC-6 SDR track. Results from a comparative ranking study, based on queries taken from AP Newswire headlines from the same time period that the Broadcast News corpus was recorded, are presented. For the AP task, retrieval accuracy is assessed by comparing the documents retrieved from ASR generated transcriptions with those from human generated transcriptions.en_US
dc.identifier.citationJ. Choi, D. Hindle, J. Hirschberg, I. Magrin-Chagnolleau, C. Nakatani, F. Pereira, A. Singhal and S. Whittaker, "An Overview of the AT&T Spoken Document Retrieval System," 1998.
dc.identifier.urihttps://hdl.handle.net/1911/20074
dc.language.isoeng
dc.subjectTemporary*
dc.subject.keywordTemporaryen_US
dc.subject.otherSignal Processing Applicationsen_US
dc.titleAn Overview of the AT&T Spoken Document Retrieval Systemen_US
dc.typeConference paper
dc.type.dcmiText
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