Evolutionary music composer integrating formal grammar

Authors:
Yaser M. A. Khalifa;Badar K. Khan;Jasmin Begovic;Airrion Wisdom;Andrew Maxymillian Wheeler
Affiliations:
State University of New York, New Paltz, NY;State University of New York, New Paltz, NY;State University of New York, New Paltz, NY;State University of New York, New Paltz, NY;State University of New York, New Paltz, NY
Venue:
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Year:
2007

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Abstract

In this paper, an autonomous music composition tool is developed using Genetic Algorithms. The production is enhanced by integrating formal grammar rules. A formal grammar is a collection of either or both descriptive or prescriptive rules for analyzing or generating sequences of symbols. In music, these symbols are musical parameters such as notes and their attributes. The composition is conducted in two Stages. The first Stage generates and identifies musically sound patterns (motifs). In the second Stage, methods to combine different generated motifs and their transpositions are applied. These combinations are evaluated and as a result, musically fit phrases are generated. Four musical phrases are generated at the end of each program run. The generated music pieces will be translated into Guido Music Notation (GMN) and have alternate representation in Musical Instrument Digital Interface (MIDI). The Autonomous Evolutionary Music Composer (AEMC) was able to create interesting pieces of music that were both innovative and musically sound.