Repository | Series | Book | Chapter
Midifind
similarity search and popularity mining in large midi databases
pp. 259-276
Abstract
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
Published in:
Aramaki Mitsuko, Derrien Olivier, Kronland-Martinet Richard, Ystad Sølvi (2014) Sound, music, and motion: 10th international symposium, CMMR 2013, Marseille, France, October 15-18, 2013. revised selected papers. Dordrecht, Springer.
Pages: 259-276
DOI: 10.1007/978-3-319-12976-1_17
Full citation:
Xia Guangyu, Huang Tongbo, Ma Yifei, Dannenberg Roger 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, 259–276.