The most relevant representations of music are notations and audio recordings, each of which emphasizes a particular perspective and promotes different approximations in the analysis and understanding of music. Linking these two representations and analysing them jointly should help to better study many musical facets by being able to combine complementary analysis methodologies. In order to develop accurate linking methods, we have to take into account the specificities of a given type of music. In this paper, we present a method for linking musically relevant sections in a score of a piece from makam music of Turkey (MMT) to the corresponding time intervals of an audio recording of the same piece. The method starts by extracting relevant features from the score and from the audio recording. The features of a given score section are compared with the features of the audio recording to find the candidate links in the audio for that score section. Next, using the sequential section information stored in the score, it selects the most likely links. The method is tested on a dataset consisting of instrumental and vocal compositions of MMT, achieving 92.1% and 96.9% -scores on the instrumental and vocal pieces, respectively. Our results show the importance of culture-specific and knowledge-based approaches in music information processing.

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).