| Paper Details: | Downloads: 445 |
| Serial Number: | P1120716001
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| Title: | Autonomous Music Composition Relying on Evolutionary Formal Grammar
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| Authors: | Yaser M.A. Khalifa, Badar K Khan, .Jasmin Begovic, Airrion Wisdom, Andrew M. Wheeler
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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.
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| Keywords: | Music, Formal Grammar, Genetic Algorithms
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| Journal/Conference: | International Journal of Artificial Intelligence and Machine Learning
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| Submission Date: | 5/1/2007 12:00:00 AM
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| Review Date: | 6/1/2007 12:00:00 AM
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| Publishing Date: | 7/1/2007 12:00:00 AM
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| Article Downloads: | 445
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