The Second International Workshop on Cross-Disciplinary and Multicultural Perspectives on Musical Rhythm and Improvisation (review)

The second International Workshop on Cross-Disciplinary and Multi-cultural Perspectives on Musical Rhythm and Improvisation was sponsored and hosted by New York University Abu Dhabi, United Arab Emirates, and took place in mid-October of 2014. Balancing theory and practice, the workshop provided a forum for a cross-disciplinary discussion of approaches to musical analysis and creation. The main aim of the workshop was to examine musical rhythm from four engaged viewpoints: music theory, musicology, and ethnomusicology; music modeling through computation; music perception and cognition; and neuroscience. Of the 41 participants who took part in this workshop, 24 were invited to give lectures about their work. The participants came from a variety of research backgrounds including musicology, psychology, neuroscience, computer science, music information retrieval (MIR), philosophy, and music composition.

The four-day program comprised 24 lectures and 3 breakout sessions, the topics for which were defined by the participants during the workshop. The participants discussed a variety of topics, including creative collaborations, data sets and evaluation, interfaces for rhythmic creation and transformation, and many more. A highlight of the conference was a concert on the first evening by saxophonist Barak Schmool, percussionists Akshay Anantapadmanabhan and Gideon Alorwoyie, and computer musicians Jaime Oliver and Gérard Assayag.

The workshop covered topics that can be broadly categorized into data and evaluation, psychology and rhythm, automatic description of musical rhythm, computer improvisation and composition, rhythm in non-Western music, and rhythm outside of music. In the following we summarize selected contributions to these categories, omitting the category “rhythm in non-Western music,” which is beyond the scope of this review.

Data and Evaluation

Most research on musicology and MIR is data driven. The choice of the right data for an experiment is crucial and often determines the outcome of an experiment. There were two breakout sessions that discussed this.

According to Xavier Serra, it is important to distinguish the terms “research corpus” from “test data set.” A research corpus is created to enable research for a set of problems and therefore is more general purpose than a test data set, which is created for a specific research question in a restricted context. It was noted that most existing corpora and data sets are not created in a consistent and standardized way. Best practices for generating annotated data sets (Peeters and Fort 2012) as well as a JavaScript Object Notation format for storing multiple annotations (Humphrey et al. 2014) have been published previously.

Apart from data, researchers also need methods to evaluate their systems and theories. This was the topic of a second breakout session. A recent paper assessed the evaluation measures currently used for audio beat-tracking tasks and showed that many measures can be improved to better match the perception of human listeners (Davies and Böck 2014). Additional research is therefore necessary to revisit current evaluation methods and to re-evaluate them using meaningful user studies.

Juan Pablo Bello talked about potential problems when using genre-annotated data sets for research on rhythmic similarity. Often, genre classification is used as a proxy for rhythmic similarity because it is hard to collect ground truth for the latter. A study on the Latin Music Database, however, showed that a high genre classification performance does not always translate into high rhythmic similarity. If the variability of the data set within a genre is too low, genre classification systems will often model rhythmically irrelevant features.

Psychology and Rhythm

The workshop had two major contributions from the fields of psychology and neuroscience. Psychologist Guy Madison presented his work on deterministic multilevel patterns (MLPs) and their uses in rhythm research. MLPs are rhythmic patterns containing multiple metrical levels—hierarchies of binary or ternary subdivisions of time. MLPs are isochronous, containing events at each associated metrical level. Where multiple...