A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity

Symbolic melodic similarity is based on measuring a pairwise distance between two songs from diverse perspectives. The distance is usually summarized as a single value for song retrieval. This obscures observing the details of similarity patterns within the two songs. In this paper, we propose a cross-scape plot representation to visualize multi-scaled melody similarity between two symbolic music. The cross-scape plot is computed by stacking up a minimum local distance between two segments from each of the two songs. As the layer goes up, the segment size increases and it computes incrementally more long-term distances. This hierarchical representation allows for capturing the location and length of similar segments between two songs in a visually intuitive manner. We show the effectiveness of the cross-scape plot by evaluating it on examples from folk music collections with similarity-based categories and plagiarism cases