Symbolic Textural Features and Melody/Accompaniment Detection in String Quartets

Music is often described as melody and accompaniment, and several MIR studies try to identify melodies. But the organization of voices is not limited to such a distinction between melody and accompaniment: Textural effects – such as repeated notes, syncopes, homorhythmy, parallel moves or imitation – underline the melody/accompaniment layout, and changes in texture usually mark structural transitions in music. We investigate how textural and other characteristics can help to identify melodic voices in polyphonic music. We select measure-level features to analyze symbolic scores of string quartets, including new textural features, and propose models to predict, on each measure, melodic and accompaniement layers in such scores, each layer possibly including several instruments. We evaluate these sets of features and the models on 12 movements in Haydn and Mozart string quartets. The best models have an average accuracy of more than 85%, taking into account both statistical and textural features.