Supervised/Unsupervised Learning for Beat Tracking (LARS)

education program·supervised student project·active

Open EPFL DCML semester, bachelor's or master's project on real-time beat prediction from performed-music MIDI using ML/AI models.

Recorded facts

Official site	https://www.epfl.ch/labs/dcml/open-positions/students/ ↗
Geography	Lausanne, Romandy, Switzerland
price	No separate fee stated; intended for eligible EPFL student-project enrollment
title	Supervised/Unsupervised Learning for Beat Tracking
format	supervised_project
topics	beat tracking; performed-music MIDI; machine learning; real-time inference; music information retrieval
duration	Project duration and credits depend on the student's EPFL project type
end date	unknown
language	English
location	EPFL, Lausanne
provider	EPFL Digital and Cognitive Musicology Lab
recurrence	Open project listing; no deadline stated
start date	unknown
instructors	Joris Monnet
program type	supervised student project
prerequisites	Musical knowledge of beat, rhythm and meter; strong Python and ML/AI experience; interest in MIR literature
program state	active
target audience	eligible EPFL students seeking a semester, bachelor's or master's project
learning outcomes	Design and evaluate a beat-prediction model for expressive performance; balance prediction accuracy and real-time efficiency
application deadline	unknown
credential or outcome	Bachelor's, semester or master's project credit subject to EPFL enrollment
scholarship and funding	No project-specific scholarship stated