Comunicació presentada a la 15th International Society for Music Information Retrieval Conference (ISMIR 2014), celebrada els dies 27 a 31 d'octubre de 2014 a Taipei, Taiwan.

Features of linguistic tone contours are important factors that shape the distinct melodic characteristics of different genres of Chinese opera. In Beijing opera, the presence of a two-dialectal tone system makes the tone-melody relationship more complex. In this paper, we propose a novel data-driven approach to analyze syllable-sized tone-pitch contour similarity in a corpus of Beijing Opera (381 arias) with statistical modeling and machine learning methods. A total number of 1,993 pitch contour units and attributes were extracted from a selection of 20 arias. We then build Smoothing Spline ANOVA models to compute matrixes of average melodic contour curves by tone category and other attributes. A set of machine learning and statistical analysis methods are applied to 30-point pitch contour vectors as well as dimensionality-reduced representations using Symbolic Aggregate approXimation(SAX). The results indicate an even mixture of shapes within all tone categories, with the absence of evidence for a predominant dialectal tone system in Beijing opera. We discuss the key methodological issues in melody-tone analysis and future work on pair-wise contour unit analysis.

This research was funded by the European Research Council under the European Union Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583).