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Information Retrieval Techniques for Speech Applications

  • Anni R. Coden
  • Eric W. Brown
  • Savitha Srinivasan
Conference proceedings IRTSA 2001

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2273)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Traditional Information Retrieval Techniques

  3. Spoken Document Pre-processing

    1. Eric W. Brown, Anni R. Coden
      Pages 11-22
  4. Adapting IR Techniques to Spoken Documents

    1. Oktay Ibrahimov, Ishwar Sethi, Nevenka Dimitrova
      Pages 23-35
    2. Alain Désilets, Berry de Bruijn, Joel Martin
      Pages 36-50
    3. Jing Huang, Geoffrey Zweig, Mukund Padmanabhan
      Pages 67-77
  5. Techniques for Multi-media Collections

    1. Mark Sanderson, Xiao Mang Shou
      Pages 78-85
  6. New Applications

  7. Back Matter
    Pages 109-109

About these proceedings

Introduction

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, pervasive devices suggests that text analysis and mining technologies can be applied in new domains never before considered.

Keywords

Multimedia Information Retrieval Speech Retrieval clustering document processing information retrieval multimedia speech recognition

Editors and affiliations

  • Anni R. Coden
    • 1
  • Eric W. Brown
    • 1
  • Savitha Srinivasan
    • 2
  1. 1.IBM T.J. Watson Research CenterYorktown HeightsUSA
  2. 2.IBM Almaden Research CenterSan JoseUSA

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-45637-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43156-5
  • Online ISBN 978-3-540-45637-7
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site
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