The tonic is a fundamental concept in Indian classical music/nsince it constitutes the base pitch from which a lead/nperformer constructs the melodies, and accompanying instruments/nuse it for tuning. This makes tonic identification/nan essential first step for most automatic analyses of Indian/nclassical music, such as intonation and melodic analysis,/nand raga recognition. In this paper we address the task/nof automatic tonic identification. Unlike approaches that/nidentify the tonic from a single predominant pitch track,/nhere we propose a method based on a multipitch analysis of/nthe audio. We use a multipitch representation to construct/na pitch histogram of the audio excerpt, out of which the/ntonic is identified. Rather than manually define a template,/nwe employ a classification approach to automatically learn/na set of rules for selecting the tonic. The proposed method/nreturns not only the pitch class of the tonic but also the precise/noctave in which it is played. We evaluate the approach/non a large collection of Carnatic and Hindustani music, obtaining/nan identification accuracy of 93%. We also discuss/nthe types of errors made by our proposed method, as well/nas the challenges in generating ground truth annotations.

This research/nwas funded by the Programa de Formación del Profesorado/nUniversitario (FPU) of the Ministerio de Educación de España and the European Research Council under/nthe European Union’s Seventh Framework Programme/n(FP7/2007-2013) / ERC grant agreement 267583 (Comp-/nMusic).