Computational Similarity of Portuguese Folk Melodies Using Hierarchical Reduction
Nádia Carvalho, Daniel Diogo, Gilberto Bernardes · 2023
We propose a method for computing the similarity of symbolically-encoded Portuguese folk melodies. The main novelty of our method is the use of a preprocessing melodic reduction at multiple hierarchies to filter the surface of folk melodies according to 1) pitch stability, 2) interval salience, 3) beat strength, 4) durational accents, and 5) the linear combination of all former criteria. Based on the salience of each note event per criteria, we create three melodic reductions with three different levels of note retention. We assess the degree to which six folk music similarity measures at multiple reduction hierarchies comply with collected ground truth from experts in Portuguese folk music. The results show that SIAM combined with 75th quantile reduction using the combined or durational accents best models the similarity for a corpus of Portuguese folk melodies by capturing approximately 84-90% of the variance observed in ground truth annotations.