Information Retrieval Techniques for Speech Applications / edited by Anni R. Coden, Eric W. Brown, Savitha Srinivasan.

Format:

Book

Contributor:

Coden, Anni R., editor.

Brown, Eric W., editor.

Srinivasan, Savitha, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science 0302-9743 ; 2273.

Lecture Notes in Computer Science, 0302-9743 ; 2273

Language:

English

Subjects (All):

Information storage and retrieval.

Natural language processing (Computer science).

Information Storage and Retrieval.

Natural Language Processing (NLP).

Local Subjects:

Information Storage and Retrieval.

Natural Language Processing (NLP).

Physical Description:

1 online resource (XII, 116 pages).

Edition:

First edition 2002.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.

System Details:

text file PDF

Summary:

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.

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).

Other Format:

Printed edition:

ISBN:

978-3-540-45637-7

9783540456377

Access Restriction:

Restricted for use by site license.