Music Genre Categorization
in the so-called "computer music" (ie not only Electronic Music or music
composed on computer, but every kind of music that can be represented in
electronic formats) are not only in the direction of
music performance and reproduction. Even before the great diffusion of Personal
Winograd discussed a "Linguistic Analysis"
of Tonal Harmony for Computers, indicating a grammatical
way to music description, that it
is one of the most typical and abstract approach to music.
However, this introduces some problems, concerning
a principled generative view on musical elements and
categories, but derived from an
a priori perspective.
the evolution of Artificial Intelligence
studies suggest to abandon a static grammar-based
definition and concentrate on the representational
aspects that should not be postulated a priori,
but acquired by experience. The aim of this reasearch is to
explore the possibility of applying a machine learning perspective on the
acquisition of prototypical musical properties characterizing music classes (like
genres) from living examples, of instances of reference
classes. Such an inductive approach has benefits
on a methodological ground and also supports a variety of useful research lines,
looking at the aggregation of existing repositories and the analysis of virtual
communities (e.g. customers, buyers, of similar music material), explaning
models for technical and social aspects of genre development and definition.
- Roberto Basili
- Armando Stellato
- Alfredo Serafini
- ... several volunteers and students
|Symbolic Music Representation and Genre Categorization
|Audio and Genre Categorization
|Kernel Methods and SVMs for music genre categorization