Xref: utzoo comp.music:911 comp.ai.neural-nets:1488
Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!samsung!usc!aero!robert
From: robert@aerospace.aero.org (Bob Statsinger)
Newsgroups: comp.music,comp.ai.neural-nets
Subject: NN's and Music, and a Question (was Music by Kohonen's NN)
Keywords: neural nets, music
Message-ID: <68750@aerospace.AERO.ORG>
Date: 14 Mar 90 18:51:22 GMT
References: <1990Mar6.200147.21195@cec1.wustl.edu> <76@nrl-cmf.UUCP> <12355@venera.isi.edu>
Reply-To: robert@aero.UUCP (Bob Statsinger)
Organization: Ahh...wouldntya like to know!
Lines: 31

In article <12355@venera.isi.edu> smoliar@vaxa.isi.edu.UUCP (Stephen Smoliar) writes:
>
>Readers more interested in what can be done with neural networks may wish to
>check out Peter Todd's contribution to the 1988 Connectionist Models Summer
>School.  Todd is a psychologist, and he seems more concerned with modeling
>phenomena which have been observed in psychological experiments.  I would
>say there is still some doubt as to how relevant those experiments are to
>music as it is actually practiced, but at least Todd appears to be approaching
>the problem more scientifically.

	The two most recent issues (vols 12 and 13) of "Computer Music
Journal" are completely devoted to neural nets and connectionism as
applied to musical composition and models of music perception. Todd has a
GREAT article in vol 13 on a recurrent network he developed for
algorithmic composition. There are also backpropagation models of
pitch perception (Jenkins), bidirectional linear nets for 
inferring tonality (Bharucha), and in vol 12 an ART system 
for musical classification.

	This semester I am working on applying invariant object recognition
to attempt to model the recognition of musical melody independent of
key signature (invariance with respect to tempo and mild distortion
invariance are also desirable). I have not seen this attempted anywhere 
in the literature that I've seen so far. If anyone has seen such an attempt,
PLEASE respond in a followup posting and/or by e-mail. Thanx much.

-- 
Bob Statsinger 				Robert@aerospace.aero.org

	The employers expressed herein are strictly mine and are
	not necessarily those of my opinion's....uh..er...whatever...