Content-based retrieval of audio in news broadcasts

Ebru Doǧan, Mustafa Sert, Adnan YazIcI

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper describes a complete, scalable and extensible content-based retrieval system for news broadcasts. Depending on segmentation results of the selected audio data, our system allows users to query audio data semantically by using both domain based fuzzy classes (anchor, commercial, reporter, sports, transition, weatherforecast, and venuesound) and similarity search. Two kinds of experiments were conducted on audio tracks of TRECVID news broadcasts to evaluate performance of the proposed query-by-example technique. The results obtained from our experiments demonstrate that Audio Spectrum Flatness feature in MPEG-7 standard performs better in music audio samples compared to other kinds of audio samples and the system is robust under different conditions.

Original languageEnglish
Title of host publicationFlexible Query Answering Systems - 8th International Conference, FQAS 2009, Proceedings
Pages548-559
Number of pages12
DOIs
Publication statusPublished - 2009
Event8th International Conference on Flexible Query Answering Systems, FQAS 2009 - Roskilde, Denmark
Duration: Oct 26 2009Oct 28 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5822 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Flexible Query Answering Systems, FQAS 2009
Country/TerritoryDenmark
CityRoskilde
Period10/26/0910/28/09

Keywords

  • Audio retrieval
  • Fuzzy classes
  • News broadcasts
  • Query-by-example

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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