Audio-Based Melody Categorization: Exploring Signal Representations and Evaluation Strategies

Melody categorization refers to the task of grouping a set of melodies into categories of similar items that originate from the same melodic contour. From a computational perspective, automatic melody categorization is of crucial importance for the automatic organization of databases, as well as for large-scale musicological studies—in particular, in the context of folk music and non-Western music traditions. We investigate methods starting from the raw audio file. For each recording contained in a collection, we extract a pitch sequence representing the main melodic line. We then estimate pairwise similarities and evaluate the discriminative power of the resulting similarity matrix with respect to ground-truth annotations. We propose novel evaluation methodologies, compare melody representations, and explore the potential of our approach in the context of two applications: interstyle and intrastyle categorization of flamenco music and tune-family recognition of folk-song recordings.