Tonic is a fundamental concept in many music traditions/nand its automatic identification should be relevant for establishing/nthe reference pitch when we analyse the melodic/ncontent of the music. In this paper, we present two methodologies/nfor the identification of the tonic in audio recordings/nof makam music of Turkey, both taking advantage/nof some score information. First, we compute a prominent/npitch and a audio kernel-density pitch class distribution/n(KPCD) from the audio recording. The peaks in the/nKPCD are selected as tonic candidates. The first method/ncomputes a score KPCD from the monophonic melody extracted/nfrom the score. Then, the audio KPCD is circularshifted/nwith respect to each tonic candidate and compared/nwith the score KPCD. The best matching shift indicates the/nestimated tonic. The second method extracts the monophonic/nmelody of the most repetitive section of the score./nNormalising the audio prominent pitch with respect to each/ntonic candidate, the method attempts to link the repetitive/nstructural element given in the score with the respective/ntime-intervals in the audio recording. The result producing/nthe most confident links marks the estimated tonic./nWe have tested the methods on a dataset of makam music/nof Turkey, achieving a very high accuracy (94.9%) with/nthe first method, and almost perfect identification (99.6%)/nwith the second method. We conclude that score informed/ntonic identification can be a useful first step in the computational/nanalysis (e.g. expressive analysis, intonation analysis,/naudio-score alignment) of music collections involving/nmelody-dominant content.

This work is partly supported by the European Research/nCouncil under the European Union’s Seventh Framework/nProgram, as part of the CompMusic project (ERC grant/nagreement 267583).