Using Statistical Models and Evolutionary Algorithms in Algorithmic Music Composition

Ajoodha, Ritesh; Jakovljević, Maria

doi:10.4018/978-1-4666-5888-2.ch597

Cited by 4 publications

(2 citation statements)

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“…Therefore, Computational Creativity (CC) can be considered as an emerging branch of artificial intelligence (AI) that studies and exploits the potential of computers to be more than feature-rich tools, and to act as autonomous creators and co-creators in their own right. Proposals are made in different artistic fields, such as visual arts [ 2 , 3 ], narrative [ 4 , 5 ] and music [ 6 , 7 ].…”

Section: Related Work In the Field Of Music Generationmentioning

confidence: 99%

“…The rapid evolution of Artificial Intelligence in recent years, has attracted the interest of researchers in Computer Sciences and Arts to the field of Artificial Creativity. This discipline uses technology to imitate the human creative process with the aim of generating works of art [ 1 ], state of the art proposals are concerned with several artistic fields, such as visual arts [ 2 , 3 ], narrative [ 4 , 5 ] and music [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

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Sensoring a Generative System to Create User-Controlled Melodies

Navarro-Cáceres

Hashimoto

González

et al. 2018

Sensors

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The automatic generation of music is an emergent field of research that has attracted the attention of countless researchers. As a result, there is a broad spectrum of state of the art research in this field. Many systems have been designed to facilitate collaboration between humans and machines in the generation of valuable music. This research proposes an intelligent system that generates melodies under the supervision of a user, who guides the process through a mechanical device. The mechanical device is able to capture the movements of the user and translate them into a melody. The system is based on a Case-Based Reasoning (CBR) architecture, enabling it to learn from previous compositions and to improve its performance over time. The user uses a device that allows them to adapt the composition to their preferences by adjusting the pace of a melody to a specific context or generating more serious or acute notes. Additionally, the device can automatically resist some of the user’s movements, this way the user learns how they can create a good melody. Several experiments were conducted to analyze the quality of the system and the melodies it generates. According to the users’ validation, the proposed system can generate music that follows a concrete style. Most of them also believed that the partial control of the device was essential for the quality of the generated music.

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