A generic audio identification system for radio broadcast monitoring based on data-driven segmentation

  • Houssemeddine Khemiri
  • , Dijana Petrovska-Delacrétaz
  • , Gérard Chollet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a generic audio identification system is introduced to identify advertisements and songs in radio broadcast streams using automatically acquired segmental units. A new fingerprinting method based on ALISP datadriven segmentation is presented. A modified BLAST algorithm is also proposed for fast and approximate matching of ALISP sequences. To detect commercials and songs, ALISP transcriptions of references composed of large library of commercials and songs, are compared to the transcriptions of the test radio stream using Levenshtein distance. The system is described and evaluated on broadcast audio streams from 12 French radio stations. For advertisement identification, a mean precision rate of 100% with the corresponding recall value of 98% were achieved. For music identification, a mean precision rate of 100% with the corresponding recall value of 95% were achieved.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE International Symposium on Multimedia, ISM 2012
Pages427-432
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Event14th IEEE International Symposium on Multimedia, ISM 2012 - Irvine, CA, United States
Duration: 10 Dec 201212 Dec 2012

Publication series

NameProceedings - 2012 IEEE International Symposium on Multimedia, ISM 2012

Conference

Conference14th IEEE International Symposium on Multimedia, ISM 2012
Country/TerritoryUnited States
CityIrvine, CA
Period10/12/1212/12/12

Keywords

  • ALISP units
  • Audio fingerprinting
  • Audio identification
  • Data-driven audio segmentation

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