Carnovalini Filippo, Rodà Antonio
Department of Information Engineering, CSC - Centro di Sonologia Computazionale, University of Padova, Padua, Italy.
Front Artif Intell. 2020 Apr 3;3:14. doi: 10.3389/frai.2020.00014. eCollection 2020.
Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers. One of its most prolific subfields is that of Music Generation (also called Algorithmic Composition or Musical Metacreation), that uses computational means to compose music. Due to the multidisciplinary nature of this research field, it is sometimes hard to define precise goals and to keep track of what problems can be considered solved by state-of-the-art systems and what instead needs further developments. With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation. To do so, we first give a picture of the research on the definition and the evaluation of creativity, both human and computational, needed to understand how computational means can be used to obtain creative behaviors and its importance within Artificial Intelligence studies. We then review the state of the art of Music Generation Systems, by citing examples for all the main approaches to music generation, and by listing the open challenges that were identified by previous reviews on the subject. For each of these challenges, we cite works that have proposed solutions, describing what still needs to be done and some possible directions for further research.
计算创造力是一个多学科领域，旨在使计算机具备创造性行为。其成果最为丰硕的子领域之一是音乐生成（也称为算法作曲或音乐元创作），即运用计算手段进行音乐创作。由于该研究领域具有多学科性质，有时很难明确精确的目标，也难以追踪哪些问题可被视为已由先进系统解决，哪些问题仍需进一步发展。通过本次综述，我们试图为那些希望探索计算创造力和音乐生成的人提供全面的介绍。为此，我们首先描绘了关于创造力定义与评估的研究情况，包括人类创造力和计算创造力，以理解如何运用计算手段来获得创造性行为及其在人工智能研究中的重要性。接着，我们通过列举音乐生成所有主要方法的示例，并列出先前关于该主题的综述所确定的开放性挑战，来回顾音乐生成系统的现状。针对这些挑战中的每一个，我们引用了提出解决方案的相关著作，阐述了仍需开展的工作以及一些可能的进一步研究方向。
