Skip to main content

Timbral Learning for Musical Robots


Abstract The tradition of building musical robots and automata is thousands of years old. Despite this rich history, even today musical robots do not play with as much nuance and subtlety as human musicians. In particular, most instruments allow the player to manipulate timbre while playing; if a violinist is told to sustain an E, they will select which string to play it on, how much bow pressure and velocity to use, whether to use the entire bow or only the portion near the tip or the frog, how close to the bridge or fingerboard to contact the string, whether or not to use a mute, and so forth. Each one of these choices affects the resulting timbre, and navigating this timbre space is part of the art of playing the instrument. Nonetheless, this typ... (more)
Created Date 2016
Contributor Krzyzaniak, Michael Joseph (Author) / Coleman, Grisha (Advisor) / Turaga, Pavan (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Subject Robotics / Music / Computer Music / Djembe / Human-Computer Interaction / Kiki / Machine Learning / Timbre
Type Doctoral Dissertation
Extent 168 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Media Arts and Sciences 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


  Full Text
7.1 MB application/pdf
Download Count: 869

Description Dissertation/Thesis