Automatic Pitch Spelling: From Numbers to Sharps and Flats

Emilios Cambouropoulos

Austrian Research Institute for Artificial Intelligence
Schottengasse 3, 1010, Vienna, Austria

http://www.ai.univie.ac.at/~emilios

Abstract:

In this paper a computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm input is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge is required such as key signature, tonal centers, time signature, voice separation and so on. Output of the algorithm is a sequence of `correctly' spelled pitches. The algorithm was evaluated on 8 complete piano sonatas by Mozart and had a success rate that is greater than 96% (10476 pitches were spelled correctly out of 10900 notes that required accidentals ­ overall number of pitches in 8 sonatas is 40058). The proposed algorithm was also compared to and tested against other pitch spelling algorithms. Pitch spelling algorithms are important not only for applications such as musical notation software packages but also for a multitude of tonal analytical tasks such as key-finding and harmonic analysis.

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