An Intelligent Composition Algorithm for Automatic Thematic Music Generation from Extant Pieces
Recently, research on computer based music generation utilizing composition algorithm has drawn attention. The goal of this research is to produce new music, never heard before, using the algorithm developed and presented in this paper. The developed algorithm uses learning technique and probability and statistical analysis. The algorithm uses note sequences and other musical parameters such as note length, pitch, accidentals, modifications (intensity, speed), and note sequence repetition density for the preparation of a probability table that will generate new music. We used thematic music pieces (from same theme) as input music for analysis using learning followed by statistical analysis. We used MATLAB for analysis and MC Music editor for display. This research study is the first of its kind to create thematic music pieces effectively in a computer-based environment. The outcome of this research has a wide range of usage: waiting-music during automated phone-calls, background music in airports, airplanes, and restaurants, and so on. The work was extended to include variations of frequency and the shape of the note sequences for analysis.
KeywordsMachine learning MATLAB Music generation Music theory Pattern recognition Statistical analysis
I would like to acknowledge Dr. Honora Chapman, Director, Smittcamp Family Honors College, for her advice and encouragement. I would also like to acknowledge Dr. Nagy Bengiamin, Chair of Electrical and Computer Engineering and Dr. Ram Nunna, Dean of Lyles College of Engineering for providing the computing facilities for this research. I also acknowledge my parents for allowing us to accomplish part of this research in a home computing system.
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