Efficient repeating pattern finding in music databases
Proceedings of the seventh international conference on Information and knowledge management
Repeating pattern discovery and structure analysis from acoustic music data
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Dominant feature vectors based audio similarity measure
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Discovering nontrivial repeating patterns in music data
IEEE Transactions on Multimedia
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In this paper, an effective method to discover repeating pattern from audio is proposed. Since the previous feature extraction methods are usually process monophony audio, for extracting more descriptive features from polyphony audio, Gabor filters bank is introduced. Meanwhile the measure criteria is suggested for qualitatively and quantitatively weighting the discernibility of extracted features. In addition, the presented algorithm is based on the incremental match and has time complexity O(nlog(n)). Experimental evaluations show that our proposed method could extract complete and meaningful repeating patterns from polyphony audio.