Composition identification in Ottoman-Turkish makam music using transposition-invariant partial audio-score alignment

Abstract

The composition information of audio recordings is highly valuable for many tasks such as automatic music description and music discovery. Given a music collection, two typical scenarios are retrieving the composition(s) performed in an audio recording and retrieving the audio recording( s), where a composition is performed. We present a composition identification methodology for these two tasks, which makes use of music scores. Our methodology first attempts to align a fragment of the music score of a composition with an audio recording. Next, it computes a similarity from the best obtained alignment. True audio-score pair emits a high similarity value. We repeat this procedure between all audio recordings and music scores, and filter the true pairs by a simple approach using logistic regression. The methodology is specialized according to the cultural-specific aspects of Ottoman-Turkish makam music (OTMM), achieving 0.96 and 0.95 mean average precision (MAP) for composition retrieval and performance retrieval tasks, respectively. We hope that our method would be useful in creating semantically linked music corpora for cultural heritage and preservation, semantic web applications and musicological studies.