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Multimedia Information Retrieval

Content-Based Information Retrieval from Large Text and Audio Databases

  • Book
  • © 1997

Overview

Authors:
  1. Peter Schäuble

    1. Swiss Federal Institute of Technology (ETH), Zurich, Switzerland

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 397)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-ix
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  2. Introduction

    • Peter Schäuble
    Pages 1-32

  3. Probabilistic Retrieval

    • Peter Schäuble
    Pages 33-47

  4. Text Retrieval

    • Peter Schäuble
    Pages 49-59

  5. Automatic Speech Recognition

    • Peter Schäuble
    Pages 61-120

  6. Speech Retrieval

    • Peter Schäuble
    Pages 121-138

  7. Case Study: Retrieving Scanned Library Cards

    • Peter Schäuble
    Pages 139-155

  8. Integrating Information Retrieval and Database Functions

    • Peter Schäuble
    Pages 157-170

  9. Outlook

    • Peter Schäuble
    Pages 171-172

  10. Back Matter

    Pages 173-190
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Keywords

About this book

Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases addresses the future need for sophisticated search techniques that will be required to find relevant information in large digital data repositories, such as digital libraries and other multimedia databases. Because of the dramatically increasing amount of multimedia data available, there is a growing need for new search techniques that provide not only fewer bits, but also the most relevant bits, to those searching for multimedia digital data. This book serves to bridge the gap between classic ranking of text documents and modern information retrieval where composite multimedia documents are searched for relevant information.
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases begins to pave the way for speech retrieval; only recently has the search for information in speech recordings become feasible. This book provides the necessary introduction to speech recognition while discussing probabilistic retrieval and text retrieval, key topics in classic information retrieval. The book then discusses speech retrieval, which is even more challenging than retrieving text documents because word boundaries are difficult to detect, and recognition errors affect the retrieval effectiveness. This book also addresses the problem of integrating information retrieval and database functions, since there is an increasing need for retrieving information from frequently changing data collections which are organized and managed by a database system.
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases serves as an excellent reference source and may be used as a text for advanced courses on the topic.

Authors and Affiliations

  • Swiss Federal Institute of Technology (ETH), Zurich, Switzerland

    Peter Schäuble

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