language: en

Technical Report CSRP-98-13
School of Computer Science, The University of Birmingham

GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters

Brad Johanson
Stanford University
Rains Apt. 9A 704 Campus Dr. Stanford, CA. 94305
bjohanso@stanford.edu

[650-497-7543]

Riccardo Poli
University of Birmingham School of Computer Science The University of Birmingham
Birmingham B15 2TT
R.Poli@cs.bham.ac.uk

[+44-121-414-3739]

Abstract In this paper we present the GP-Music System, an interactive system which allows users to evolve short musical sequences using interactive genetic programming, and its extensions aimed at making the system fully automated. The basic GP-system works by using a genetic programming algorithm, a small set of functions for creating musical sequences, and a user interface which allows the user to rate individual sequences. With this user interactive technique it was possible to generate pleasant tunes over runs of 20 individuals over 10 generations. As the user is the bottleneck in interactive systems, the system takes rating data from a users run and uses it to train a neural network based automatic rater, or auto rater, which can replace the user in bigger runs. Using this auto rater we were able to make runs of up to 50 generations with 500 individuals per generation. The best of run pieces generated by the auto raters were pleasant but were not, in general, as nice as those generated in user interactive runs.

1 Introduction