Information Retrieval Techniques for Speech Applications (Record no. 188567)

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001 - CONTROL NUMBER
control field 978-3-540-45637-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423132518.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540456377
-- 978-3-540-45637-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/3-540-45637-6
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA75.5-76.95
072 #7 - SUBJECT CATEGORY CODE
Subject category code UNH
Source bicssc
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Subject category code UND
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Subject category code COM030000
Source bisacsh
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Subject category code UNH
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code UND
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 025.04
Edition number 23
245 10 - TITLE STATEMENT
Title Information Retrieval Techniques for Speech Applications
Medium [electronic resource] /
Statement of responsibility, etc edited by Anni R. Coden, Eric W. Brown, Savitha Srinivasan.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2002.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2002.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 116 p.
Other physical details online resource.
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490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume number/sequential designation 2273
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Traditional Information Retrieval Techniques -- Perspectives on Information Retrieval and Speech -- Spoken Document Pre-processing -- Capitalization Recovery for Text -- Adapting IR Techniques to Spoken Documents -- Clustering of Imperfect Transcripts Using a Novel Similarity Measure -- Extracting Keyphrases from Spoken Audio Documents -- Segmenting Conversations by Topic, Initiative, and Style -- Extracting Caller Information from Voicemail -- Techniques for Multi-media Collections -- Speech and Hand Transcribed Retrieval -- New Applications -- The Use of Speech Retrieval Systems: A Study Design -- Speech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition -- WASABI: Framework for Real-Time Speech Analysis Applications (Demo).
520 ## - SUMMARY, ETC.
Summary, etc This volume is based on a workshop held on September 13, 2001 in New Orleans, LA, USA as part of the24thAnnualInternationalACMSIGIRConferenceon ResearchandDevelopmentinInformationRetrieval.Thetitleoftheworkshop was: “Information Retrieval Techniques for Speech Applications.” Interestinspeechapplicationsdatesbackanumberofdecades.However, it is only in the last few years that automatic speech recognition has left the con?nes of the basic research lab and become a viable commercial application. Speech recognition technology has now matured to the point where speech can be used to interact with automated phone systems, control computer programs, andevencreatememosanddocuments.Movingbeyondcomputercontroland dictation, speech recognition has the potential to dramatically change the way we create,capture,andstoreknowledge.Advancesinspeechrecognitiontechnology combined with ever decreasing storage costs and processors that double in power every eighteen months have set the stage for a whole new era of applications that treat speech in the same way that we currently treat text. The goal of this workshop was to explore the technical issues involved in a- lying information retrieval and text analysis technologies in the new application domainsenabledbyautomaticspeechrecognition.Thesepossibilitiesbringwith themanumberofissues,questions,andproblems.Speech-baseduserinterfaces create di?erent expectations for the end user, which in turn places di?erent - mands on the back-end systems that must interact with the user and interpret theuser’scommands.Speechrecognitionwillneverbeperfect,soanalyses- plied to the resulting transcripts must be robust in the face of recognition errors. The ability to capture speech and apply speech recognition on smaller, more - werful, pervasivedevices suggests that text analysis and mining technologies can be applied in new domains never before considered.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information storage and retrieval systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural language processing (Computer science).
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information Storage and Retrieval.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural Language Processing (NLP).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Coden, Anni R.
Relator term editor.
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Brown, Eric W.
Relator term editor.
Relator code edt
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700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Srinivasan, Savitha.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540431565
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783662161975
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
-- 1611-3349 ;
Volume number/sequential designation 2273
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/3-540-45637-6">https://doi.org/10.1007/3-540-45637-6</a>
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Koha item type eBooks-CSE-Springer

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