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(2014) Sound, music, and motion, Dordrecht, Springer.
Midifind
similarity search and popularity mining in large midi databases
Guangyu Xia, Tongbo Huang, Yifei Ma, Roger B. Dannenberg
pp. 259-276
While there are perhaps millions of MIDI files available over the Internet, it is difficult to find performances of a particular piece because well labeled metadata and indexes are unavailable. We address the particular problem of finding performances of compositions for piano, which is different from often-studied problems of Query-by-Humming and Music Fingerprinting. Our MidiFind system is designed to search a million MIDI files with high precision and recall. By using a hybrid search strategy, it runs more than 1000 times faster than naive competitors, and by using a combination of bag-of-words and enhanced Levenshtein distance methods for similarity, our system achieves a precision of 99.5 % and recall of 89.8 %.
Publication details
DOI: 10.1007/978-3-319-12976-1_17
Full citation:
Xia, G. , Huang, T. , Ma, Y. , Dannenberg, R. B. (2014)., Midifind: similarity search and popularity mining in large midi databases, in M. Aramaki, O. Derrien, R. Kronland-Martinet & S. Ystad (eds.), Sound, music, and motion, Dordrecht, Springer, pp. 259-276.
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