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Announcement of Connection Science issue on Music and Creativity

Dear List -

Niall Griffith sent me the following announcement of a very interesting-
sounding issue of Connection Science.

--  DAn Ellis <dpwe@media.mit.edu>
    MIT Media Lab Perceptual Computing - Machine Listening group.

------- Forwarded Message
From: ngr@dcs.exeter.ac.uk
Date: Fri, 17 Feb 95 19:20:24 GMT
Subject: Posting Request

 Special Issue of Connection Science on Music and Creativity

We thought people would like to know that a new collection of work on
connectionist models of musical cognition and artistic creativity has
appeared in print this month.  The collection is a double issue of the
journal Connection Science, volume 6, nos. 2&3, covering aspects of
musical perception, conception, and action, and the generation of
visual art.  Some of the papers in this double issue are very
interesting from a computational point of view as well, beyond their
specific application domain.  We hope you enjoy the issue and find it
useful, and we welcome your comments and updates about further work in
this area for future collections such as this.

Niall Griffith and Peter Todd

(Please note: Single copies of this double issue are available. A book
version of this double issue is also planned for the near future.)

Niall Griffith,
Department of Computer Science,
University of Exeter,
Prince of Wales Road,
Exeter, EX4 4PT  UK
Email: ngr@dcs.exeter.ac.uk

Peter Todd
Department of Psychology
University of Denver
2155 S. Race Street
Denver, CO  80208  USA
Email: ptodd@edu.du.psy

Contents of Connection Science 6(2-3), 1994:

0.  Niall Griffith & Peter Todd
    Editorial: Process and representation in connectionist models of
     musical structure

1.  Ian Taylor & Mike Greenhough
    Modelling pitch perception with adaptive resonance theory
     artificial networks

2.  Niall Griffith
    Developing tonal centres and abstract pitch as categorisations of

3.  Edward Large & John Kolen
    Resonance and the perception of musical meter

4.  Steven Smoliar
    Modelling musical perception: A critical view

5.  Michael Page
    Modelling the perception of musical sequences with self-organizing
     neural networks

6.  Michael Mozer
    Neural network music composition by prediction: Exploring the
     benefits of psychoacoustic constraints and multiscale processing

7.  Matthew Bellgard & C. Tsang
    Harmonizing music the Boltzmann way

8.  Bruce Katz
    An ear for melody

9.  Shumeet Baluja, Dean Pomerleau & Todd Jochem
    Towards automated artificial evolution for computer generated images

10. Michael Casey
    Understanding musical sound with forward models and physical models

------- End of Forwarded Message