Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
MUSICAL STYLE PERCEPTION BY A LINEAR AUTO-ASSOCIATOR MODEL AND HUMAN LISTENERS
 

Summary: MUSICAL STYLE PERCEPTION BY A LINEAR AUTO-ASSOCIATOR
MODEL AND HUMAN LISTENERS
Barbara Tillmann*
Hervé Abdi **
W. Jay Dowling **
* CNRS-UMR 5020, Lyon, France
** University of Texas at Dallas, USA
ABSTRACT
The present research adapts to musical style perception a
simulation approach previously used with visual stimuli (i.e.,
faces), which can handle a variety of tasks such as identification,
recognition and categorization. A linear auto-associator was
trained with musical excerpts of three composers (Bach, Mozart,
and Beethoven). Based on its learned representation, a linear
classifier (i.e., Adaline) was trained and its ability to categorize
new excerpts from these three composers was evaluated. A subset
of the excerpts used to train the linear models is currently tested in
free and constrained classification tasks with human listeners.
1. INTRODUCTION
Musical Style Perception

  

Source: Abdi, Hervé - School of Behavioral and Brain Sciences, University of Texas at Dallas

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences