rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Information Retrieval Techniques for Speech Applications
  name:
    name part: Coden, Anni R.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Brown, Eric W.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Srinivasan, Savitha.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2002
    edition: 1st ed. 2002.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 116 p. online resource.
  abstract: 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.
  table of contents: 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).
  note: edited by Anni R. Coden, Eric W. Brown, Savitha Srinivasan.
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Natural language processing (Computer science)
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Natural Language Processing (NLP)
  classification: QA75.5-76.95
  classification: 025.04
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 2273
  identifier: 9783540456377
  identifier: https://doi.org/10.1007/3-540-45637-6
  record info:
    record creation date: 121227
    record change date: 20191027132626.0
    record identifier: 978-3-540-45637-7