Comunicació presentada a la International Computer Music Conference, ICMC/SMC, celebrada a Atenes (Grècia) del 14 al 20 de setembre de 2014.

Musical melodies contain hierarchically organized events, where some events are more salient than others, acting as melodic landmarks. In Hindustani music melodies, an important landmark is the occurrence of a nyas. Occurrence of nyas is crucial to build and sustain the format of a r¯ag and mark the boundaries of melodic motifs. Detection of ny¯as segments is relevant to tasks such as melody segmentation, motif discovery and r¯ag recognition. However, detection of ny¯as segments is challenging as these segments do not follow explicit set of rules in terms of segment length, contour characteristics, and melodic context. In this paper we propose a method for the automatic detection of nyas segments in Hindustani music melodies. It consists of two main steps: a segmentation step that incorporates domain knowledge in order to facilitate the placement of nyas boundaries, and a segment classification step that is based on a series of musically motivated pitch contour features. The proposed method obtains significant accuracies for a heterogeneous data set of 20 audio music recordings containing 1257 nyas svar occurrences and total duration of 1.5 hours. Further, we show that the proposed segmentation strategy significantly improves over a classical piece-wise linear segmentation approach.

This work is partly supported by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583). J.S. acknowledges 2009-SGR-1434 from Generalitat de Catalunya, ICT-2011-8-318770 from the European Commission, JAEDOC069/2010 from CSIC, and European Social Funds.