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{ "item_title" : "Information Retrieval Techniques for Speech Applications", "item_author" : [" Anni R. Coden", "Eric W. Brown", "Savitha Srinivasan "], "item_description" : "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/54/043/156/354043156X_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Information Retrieval Techniques for Speech Applications|Anni R. Coden

Information Retrieval Techniques for Speech Applications

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Overview

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.

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Details

  • ISBN-13: 9783540431565
  • ISBN-10: 354043156X
  • Publisher: Springer
  • Publish Date: January 2002
  • Dimensions: 9.21 x 6.14 x 0.27 inches
  • Shipping Weight: 0.42 pounds
  • Page Count: 116

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