A Novel Automatic Composition System Using Evolutionary Algorithm and Phrase Imitation

Music is a significant achievement of human activities and culture. Composing music is a complex and challenging task in that many factors, such as scale, key, chord, rhythm, and pitch, and their interactions need to be considered. With the advance of computer technology and artificial intelligence, automatic composition systems emerge and present some promising results. In particular, composing music through evolutionary algorithms has received increasing attention. Although evolutionary approaches are capable of generating compositions that follow music theory, these compositions are easily recognized as machine-made products due to their unpredictability in melodic progression, which is an important factor affecting a human's impression and feeling on a song. This paper aims for an automatic composition system that emulates human intelligence in music composition. Specifically, we propose the phrase imitation-based evolutionary composition (PIEC) to generate compositions by an evolutionary algorithm based on music theory and imitation of the characteristics and melodic progression of human-composed music. The PIEC conducts intraphrase and interphrase rearrangement to imitate the ascending/descending motion of phrases. Furthermore, we design four fitness functions for the PIEC to evolve compositions considering note distribution, interval variance, and music theory. The experimental results show that the proposed PIEC can effectively generate satisfactory compositions with the characteristics of the sample melody. The results also validate the effects of phrase imitation and the four fitness functions on evolutionary composition.