Download e-book for kindle: Information Retrieval Techniques for Speech Applications by James Allan (auth.), Anni R. Coden, Eric W. Brown, Savitha

By James Allan (auth.), Anni R. Coden, Eric W. Brown, Savitha Srinivasan (eds.)

ISBN-10: 354043156X

ISBN-13: 9783540431565

This quantity relies on a workshop hung on September thirteen, 2001 in New Orleans, los angeles, united states as a part of the24thAnnualInternationalACMSIGIRConferenceon ResearchandDevelopmentinInformationRetrieval.Thetitleoftheworkshop was once: “Information Retrieval suggestions for Speech Applications.” Interestinspeechapplicationsdatesbackanumberofdecades.However, it's only within the previous few years that automated speech reputation has left the con?nes of the fundamental study lab and develop into a potential advertisement program. Speech acceptance expertise has now matured to the purpose the place speech can be utilized to have interaction with computerized cell structures, keep an eye on machine courses, andevencreatememosanddocuments.Movingbeyondcomputercontroland dictation, speech attractiveness has the capability to dramatically swap the way in which we create,capture,andstoreknowledge.Advancesinspeechrecognitiontechnology mixed with ever lowering garage expenditures and processors that double in strength each eighteen months have set the degree for an entire new period of purposes that deal with speech within the comparable approach that we at the moment deal with textual content. The objective of this workshop was once to discover the technical matters all in favour of a- mendacity info retrieval and textual content research applied sciences within the new program domainsenabledbyautomaticspeechrecognition.Thesepossibilitiesbringwith themanumberofissues,questions,andproblems.Speech-baseduserinterfaces create di?erent expectancies for the top person, which in flip areas di?erent - mands at the back-end platforms that needs to have interaction with the consumer and interpret theuser’scommands.Speechrecognitionwillneverbeperfect,soanalyses- plied to the ensuing transcripts needs to be strong within the face of popularity mistakes. the facility to trap speech and observe speech acceptance on smaller, extra - werful, pervasive units means that textual content research and mining applied sciences may be utilized in new domain names by no means sooner than considered.

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Therefore, owners of multimedia assets can afford to invest significant resources into manually tagging and indexing this content to make it searchable and browsable online. We would like to thank Peter Turney for his helpful insights regarding the Extractor system. R. W. Brown, and S. , LNCS 2273, pp. 36–50, 2002. c Springer-Verlag Berlin Heidelberg 2002 Extracting Keyphrases from Spoken Audio Documents 37 Widespread deployment of broadband technologies will likely accelerate the growth of online multimedia content because it will allow more people to use or even produce and distribute such content.

Martin, and M. A. Przybocki. 1998 broadcast news benchmark test results. In Proc. of the 1999 DARPA Broadcast News Workshop, Herndon, VA, 1999. [13] M. A. Przybocki, J. G. Fiscus, J. S. Garofolo, and D. S. Pallett. 1998 hub-4 information extraction evaluation. In Proc. of the 1999 DARPA Broadcast News Workshop, Herndon, VA, 1999. [14] Y. Ravin and C. Leacock. Polysemy: Theoretical and Computational Approaches. Oxford University Press, 2000. [15] Y. Ravin, N. Wacholder, and M. Choi. Disambiguation of names in text.

Another constant K may be viewed as a discounting parameter on the word frequency: when K is 0, the combined weight reduces to the collection frequency weight; as K increases the combined weight asymptotically approaches tf ∗ itf [21]. In our case K is equal to 2. Now, in accordance with assumptions stated above, we can easily get the weight of a document and weights of any of its parts via applying the formula (2). DW (Di ) = CW (wk ) (2) wk ∈Di To obtain common words between documents, we consider the fact that not all words in documents are equally informative.

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Information Retrieval Techniques for Speech Applications by James Allan (auth.), Anni R. Coden, Eric W. Brown, Savitha Srinivasan (eds.)


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