Comparing pitch spelling algorithms

A pitch spelling algorithm predicts the pitch names of the notes in a musical passage when given the onset-time, MIDI note number and possibly the duration and voice of each note. Various versions of the algorithms of Longuet-Higgins, Cambouropoulos, Temperley and Sleator, Chew and Chen, and Meredith were run on a corpus containing 195972 notes, equally divided between eight classical and baroque composers. The standard deviation of the accuracies achieved by each algorithm over the eight composers was used as a measure of its style dependence (SD). Meredith's ps1303 was the most accurate algorithm, spelling 99.43% of the notes correctly (SD = 0.54). The best version of Chew and Chen's algorithm was the least dependent on style (SD = 0.35) and spelt 99.15% of the notes correctly. A new version of Cambouropoulos's algorithm, combining features of all three versions described by Cambouropoulos himself, also spelt 99.15% of the notes correctly (SD = 0.47). The best version of Temperley and Sleator's algorithm spelt 97.79% of the notes correctly, but nearly 70% of its errors were due to a single sudden enharmonic change. Longuet-Higgins's algorithm spelt 98.21% of the notes correctly (SD = 1.79) but only when it processed the music a voice at a time.