Anssi Klapuri - Gamified musical instrument learning: music processing techniques and learning curve optimization

Wed, 03/19/2014 - 5:15pm - 7:00pm
Rm 217, CCRMA classroom, 660 Lomita Drive, Stanford
Event Type: 
 Playing a musical instrument and playing video games share certain similarities as activities. That has enabled successful music-oriented games such as Rock Band or Guitar Hero, but even more importantly, gamified e-learning applications seem to have particularly high potential for learning certain aspects of musical instrument skills. This talk shares experiences from developing the game GuitarBots, where any real guitar is used as a game controller and the microphone signal is analyzed to figure out the user’s actions. I will describe music transcription techniques that allow sufficiently accurate real-time feedback on the user's playing, discuss how the learning curve and motivation can be optimized for users at different skill levels, and share some experiences of successful and less successful attempts at tackling this emerging area of musical instrument learning applications.


Anssi Klapuri received his Ph.D. degree from Tampere University of Technology (TUT), Tampere, Finland. He visited as a post-doctoral researcher at Ecole Centrale de Lille, France, and Cambridge Univerisity, UK, in 2005 and 2006, respectively. He worked until 2009 as a professor (pro term) at TUT. In 2009 he joined Queen Mary, University of London as a lecturer in Sound and Music Processing. In September 2011 he joined Ovelin Ltd to develop game-based musical instrument learning applications, while continuing part-time at TUT. His research interests include audio signal processing, auditory modeling, and machine learning.

Open to the Public
Syndicate content