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Abstract

This article follows step by step a general framework for fingerprint extraction in order to develop a system for advertisements' monitoring. The parameterization process uses some spatial and spectral characteristics measured over 600 advertisements that contain various types of sounds. Key factors such as accuracy, process time, and granularity are analyzed together in order to enhance the system performance. At the end, the algorithm shows an accuracy of 99% using three seconds of granularity samples, and also the best compromise between processing time and performance is achieved. This study suggests a set of parameterization steps which could be successfully implemented in other related audio applications.

Original languageEnglish
Title of host publication2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538638941
DOIs
StatePublished - 4 Jan 2018
Event2nd IEEE Ecuador Technical Chapters Meeting, ETCM 2017 - Salinas, Ecuador
Duration: 16 Oct 201720 Oct 2017

Publication series

Name2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017
Volume2017-January

Conference

Conference2nd IEEE Ecuador Technical Chapters Meeting, ETCM 2017
Country/TerritoryEcuador
CitySalinas
Period16/10/1720/10/17

Keywords

  • advertising monitoring
  • audio fingerprint
  • automatic content recognition
  • signal processing

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