The RhythMus project:
In May 2013, I started with my post-doctoral research in the context of a Marie Curie Intra-European Fellowship. I enjoyed two years with my colleagues at Boğaziçi university, and this webpage gives a short overview of results and publications that emerged from this project.
Most musics in the world are characterized by a certain amount of repetition that shapes musical time
and makes music a unique experience. This repetitive structure has a hierarchical form that consists
of sound event onsets, a more or less regular pulse, rhythmic patterns, and higher units of musical
form. While many computational analysis methods concentrate on one level of the rhythm hierarchy
in isolation, this project proposed dynamic Bayesian models for the rhythm analysis that take into
account the relations between the hierarchy levels.
Within this project, one important goal was to increase the flexibility of the state of the art in analysis
of rhythmic structure. Until the beginning of this project, most approaches were tailored towards
certain properties of Eurogenetic music. One example of such properties is the assumption of strict
isochrony of the beat pulse, which is the pulse a human listener will be most likely tap her foot to the
music. This isochrony is not common in many cultures, as, for instance, Turkish, Greek, and Indian
The developed models unify the tracking of note onsets and the most prominent beat with the
observation of similarity on a higher metrical level into one unified Bayesian analysis framework.
The advantage of this framework is the flexibility to changing signal characteristics and to
non-isochrony of the beat. The main achievement of this project was the successful development of
computational tools that are capable to determine the type of meter and to track the alignment of the
metric cycle to an unknown music signal. This works with high accuracy for various forms of meter,
and for a large variety of musical style, with the only precondition being the availability of a small
amount of annotated representative music examples that the model can be trained on.
The project reached the main objectives stated in the proposal to full extent, and did some steps to
explore the applicability of the proposed model to different analysis problems. State-of-the-art
methods for onset detection were integrated as observation models that couple the proposed Bayesian
networks to the music signal. Most importantly, a dynamic Bayesian network was implemented that
integrates the tracking process on several metrical levels. These levels can be flexibly defined, and
the observation models can be adapted to new styles easily. The existing model is capable to identify
the metrical structure of a piece, and to track it on several levels on Greek, Indian, and Turkish
musics with an accuracy that was far beyond reach before this project. On the other hand,
performance on Eurogenetic styles is equal to the best available approaches presented previously.
Several inference methods were developed that decrease the computational demands of the
developed analysis method, creating a critical mass of Bayesian inference related publications in
MIR throughout the last years.
The proposed model was adapted to melodic analysis as well, in an approach that targets the
alignment of written notation to the sound of a performance. This way, the work in this project went
beyond the targeted rhythmic aspects, and demonstrated the value of the developed models on a more
The used Bayesian models attracted the attention from several other European research groups, in
specific the Johannes Kepler University (Linz, Austria), and the University Pompeu Fabra
(Barcelona, Spain). The fellow was able to establish a network of collaboration between these
institutes, which lead to the development of shared code repositories that will be made available for
research purposes. The publication of these repositories is scheduled for the conference of the
International Society for Music Information Retrival (ISMIR) in 2015, and will represent an
important landmark of a larger international collaboration that was made feasible by the RhythMus
The outcome of this project contributes to the state of the art in Music Information Retrieval (MIR).
The proposed methods are an important contribution to music distribution and recommendation
platforms, because the models can be adapted to previously unseen styles with minimal human
expert interaction. This way, they can provide valuable information about tempo, meter type, and
timing characteristics of musical styles that were so far out of reach for automatic analysis methods.
These capabilities make the proposed models interesting for research in ethnomusicology as well,
since the proposed analysis methods in combination with appropriate visualizations can provide a
novel perspective on various aspects related to rhythm in various musics of the world.
1.: Benetos, E. & Holzapfel, A. (2015), 'Automatic transcription of Turkish microtonal music', Journal of the Acoustical Society of America, accepted for publication.
2.: Holzapfel, A. (2015), 'Relation between surface rhythm and rhythmic modes in Turkish makam music', Journal for New Music Research 44(1), 25-38.
3.: Krebs, F.; Holzapfel, A.; Cemgil, A. T. & Widmer, G. (2015), 'Inferring metrical structure in music using particle filters', IEEE Transactions on Audio, Speech and Language Processing 23(5), 817-827.
4.: Holzapfel, A. (2015), Patterns of identity: Rhythmic and melodic aspects of Cretan Leaping dances, in 'Music on Crete, Traditions of a Mediterranean island.', Vienna Series in Ethnomusicology, in press.
5.: Holzapfel, A. (2015), A corpus study on rhythmic modes in Turkish makam music and their interaction with meter, in '15. Congress of the Society for Music Theory' (Berlin, Germany), accepted.
6.: Srinivasamurthy, A.; Holzapfel, A.; Cemgil, A. T. & Serra, X. (2015), Particle Filters for Efficient Meter Tracking with Dynamic Bayesian Networks, in 'Proceedings of ISMIR - International Society for Music Information Retrieval Conference' (Malaga, Spain), accepted.
7.: Holzapfel, A. (2015), Melodic key phrases in traditional Cretan dance tunes, in 'Proceedings of the 5th Workshop on Folk Music Analysis', pp. 79-82 (Paris, France).
8.: Holzapfel, A.; Şimşekli, U.; Şentürk, S. & Cemgil, A. T. (2015), Section-level modeling of musical audio for linking performances to scores in Turkish makam music, in 'Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)' (Brisbane, Australia).
9.: Benetos, E. & Holzapfel, A. (2014), Incorporating pitch class profiles for improving automatic transcription of Turkish makam music, in 'Proceedings of the 4th Workshop on Folk Music Analysis', pp. 15-20 (Istanbul, Turkey).
10.: Fossum, D. & Holzapfel, A. (2014), Exploring the Music of Two Masters of the Turkmen Dutar Through Timing Analysis, in 'Proceedings of the 4th Workshop on Folk Music Analysis', pp. 52-56 (Istanbul, Turkey).
11.: Karaosmanoglu, M. K.; Bozkurt, B.; Holzapfel, A. & Dişiaçık, N. D. (2014), A symbolic dataset of Turkish makam music phrases, in 'Proceedings of the 4th Workshop on Folk Music Analysis', pp. 10-14 (Istanbul, Turkey).
12.: Holzapfel, A. (2014), Leaping dances in Crete: Tradition in motion, in 'Conference on Analytic Approaches to World Music' (London, UK).
13.: Holzapfel, A.; Krebs, F. & Srinivasamurthy, A. (2014), Tracking the “odd”: Meter inference in a culturally diverse music corpus, in 'Proceedings of ISMIR - International Society for Music Information Retrieval Conference', pp. 425-430 (Taipei, Taiwan).