Midifind

similarity search and popularity mining in large midi databases

Guangyu Xia

Tongbo Huang

Yifei Ma

Roger B. Dannenberg

pp. 259-276

in: Mitsuko Aramaki, Olivier Derrien, Richard Kronland-Martinet, Sølvi Ystad (eds), Sound, music, and motion, Berlin, Springer, 2014

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 %.