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Predicting Pairwise Pitch Contour Relations Based on Linguistic Tone Information in Beijing Opera Singing

Title Predicting Pairwise Pitch Contour Relations Based on Linguistic Tone Information in Beijing Opera Singing
Publication Type Conference Paper
Year of Publication 2015
Conference Name 16th International Society for Music Information Retrieval (ISMIR) Conference
Authors Zhang, S. , Caro Repetto R. , & Serra X.
Pagination 107-113
Conference Start Date 26/10/2015
Conference Location Malaga, Spain
Abstract The similarity between linguistic tones and melodic pitch contours in Beijing Opera can be captured either by the contour shape of single syllable units, or by the pairwise pitch height relations in adjacent syllable units. In this paper, we investigate the latter problem with a novel machine learning approach, using techniques from time series data mining. Approximately 1300 pairwise contour segments are extracted from a selection of 20 arias. We then formulate the problem as a supervised machine learning task of predicting types of pairwise melodic relations based on linguistic tone information. The results give a comparative view of fixed and mixed-effects models that achieved around 70% of maximum accuracy. We discuss the superiority of the current method to that of the unsupervised learning in single-syllable-unit contour analysis of similarity in Beijing Opera.
preprint/postprint document http://dblp.org/rec/conf/ismir/ZhangRS15