Composing Bossa Nova by Evolutionary Computation

Development of artificial intelligence has enabled automation of diverse complicated tasks, such as planning, scheduling, and natural language processing. As one of the complicated tasks, music composition involves various aspects, e.g., melody, rhythm, harmonization, phrasing, and forms. Evolutionary composition systems ordinarily formulate music composition as an optimization problem and adopt evolutionary algorithms to deal with it. This study focuses on evolutionary composition on a special genre—Bossa Nova. The proposed system uses integer-coded genetic algorithm to generate the melody, followed by a postprocess for arranging suitable accompaniment. In particular, the genetic algorithm features evaluation rules derived from music theory for consonant melodies. The postprocess creates a treble part and a bass part which together form the chord accompaniment on the basis of Bossa Nova harmony and rhythmic patterns. This study conducts experiments for quality verification of the generated music. Experimental results show that the proposed rules are able to guide genetic algorithm for composing harmonious melodies, and the accompaniments from postprocess blend well with the generated melodies. By and large, the integration of generated melodies and accompaniments presents satisfactory Bossa Nova music.

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