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From: chank@cb.ecn.purdue.edu (King Chan)
Newsgroups: comp.ai.neural-nets
Subject: Re: Looking for Neural Net/Music Applications
Message-ID: <939@cb.ecn.purdue.edu>
Date: 9 May 89 17:30:47 GMT
References: <937@cb.ecn.purdue.edu>
Organization: Purdue University Engineering Computer Network
Lines: 26

In article <937@cb.ecn.purdue.edu>, androula@cb.ecn.purdue.edu (Ioannis Androulakis) writes:
> long time ago. It is about the work he is doing attempting
> to have a NN learn how to do basic jazz "impovisation"
> My question is the following, how do you define "improvisation"
> and, once you do that, what do you mean by "learn how to imporovise"
> I believe that imporvisation is not the output of some neurons 
> that learned how to do something. What I do not undertstand is 
> what you expect the network to learn. If we will ever be able
>  yannis
>  androula@helium.ecn.purdue.edu  
> 
  I am aware of AI application to musical composition.  Specifically, 
  research at MIT produced interesting model-based composition programs
  for jazz, rock, and rag time.  This was on exhibit at chicago's
  museum of science and technology.              
	There is a possibility of learning even for improvisation.
  Music can be considered as a collection of primitives, patterns of 
  which make a piece of music.  The learning aspect can be spoken of 
  as the ability to pass a judgement on such a piece as being aesthetically
  appealing to a musician or not.  It is this judgement that allows a 
  adaptive approach to the development of music.  The judgement is the 
  part of the musician's knowledge that needs to be learned by the program 
  if it is to make any good improvisations.
  QED
                                                   KING CHAN
                                                   (chessnut)