Audio retrieval using timbral feature

R. Christopher Praveen Kumar, D. Abraham Chandy

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

5 Scopus citations

Abstract

The increase in availability of music information demands for the development of tools for audio retrieval. Audio information retrieval implicates the retrieval of similar audio files based on the feature. Feature extraction is one of the important tasks where the entire retrieval system relies on. In this work, audio information retrieval has been performed on GTZAN datasets using Delta Mel-Frequency Cepstral Coefficients (MFCC) feature which is a kind of timbre feature. The results obtained for the various stages of feature extraction and retrieval performance plot has been presented. The average precision and recall values obtained are 78.67% and 58.02%, respectively.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, ICE-CCN 2013
Pages222-226
Number of pages5
DOIs
StatePublished - 8 Aug 2013
Externally publishedYes
Event2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, ICE-CCN 2013 - Tirunelveli, India
Duration: 25 Mar 201326 Mar 2013

Publication series

Name2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, ICE-CCN 2013

Conference

Conference2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, ICE-CCN 2013
Country/TerritoryIndia
CityTirunelveli
Period25/03/1326/03/13

Keywords

  • Audio Retrieval
  • Feature Extraction
  • MFCC
  • Mel filter bank
  • Timbral Feature

ASJC Scopus subject areas

  • Computer Networks and Communications

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