Our Research Projects
Study of Synchronization in Javanese Gamelan Musical Performance
PIs: Stefanie Acevedo (Music), Steven Harrison (Kinesiology)
Student Collaborators: Spencer Ferris, Susan Tilbury (Psychology)
Collaborators: Maho Ishiguro & Darsono (Emory University)
This project studies sensorimotor synchronization during Javanese Gamelan performance, an Indonesian musical practice that is known for its “playability” by individuals with various levels of expertise. Javanese Gamelan represents a rich and complex social coordination phenomenon, and performances can involve multiple musicians coordinating complexly nested rhythms. Our research investigates synchronization using motion capture, EMG sensors, and behavioral experimentation. The work is done in collaboration with UConn's Kinesiology and Psychological Arts Department.
This research is supported by the following grants:
School of Fine Arts STEAM Innovation Grant 2022-2023
School of Fine Arts Research Grant 2022-2023
Understanding Harmonic Expectation of Popular Music
PIs: Stefanie Acevedo (Music), Ed Large (Psychology)
Student Collaborators: Vivian Hudson (Music)
Collaborators: Ian Quinn, Aditya Chander (Yale University)
This project includes various approaches to understanding harmonic expectation, including analytical queries of symbolic musical corpora, behavioral experiments, and neuroscientific approaches. This work relies on the assumption that we implicitly learn musical style through exposure. We use information theory methodology to segment musical events in the corpus, and behavioral methodologies to find evidentiary support for our computational models. This work is done in collaboration with members of the Yale Department of Music.
This research has been supported by the following research grants:
Yale Digital Humanities Lab Seed Grant 2017
Coordination of Movement and Sound in Bulgarian Dance
PIs: Daniel Goldberg (Music), Ed Large (Psychology), Insoo Kim (Medicine & Biomedical Engineering)
Student Collaborators: Raheli Roy (Biomedical Engineering)
Collaborators: Dilyana Kurdova (Sofia, Bulgaria)
This project involves developing and applying a system of low-cost pressure sensors inside dancers’ shoes and motion sensors on dancers’ bodies to record data about how dancers move in time with music. We use the sensor system to record movement and audio data from dancers and musicians in Bulgaria, facilitating the analysis of periodicity, phasing, and variability of dance movements in coordination with music. Bulgarian folk dance is of special interest in this regard because it includes uneven rhythmic patterns that most models of synchronization developed in the context of Western European music do not fully explain.
This research is supported by the following grants:
School of Fine Arts STEAM Innovation Grant 2019-2020