ReviewFrontiers in artificial intelligence2020
Computational Creativity and Music Generation Systems: An Introduction to the State of the Art.
Review in Frontiers in artificial intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- From traditional musicians to digital musicians: a study on talent transformation in the music industries driven by AI technology.Frontiers in sociology · 2026Article
- AI-assisted feedback and reflection in vocal music training: effects on metacognition and singing performance.Frontiers in psychology · 2025Article
- Latent evolutionary signatures: a general framework for analysing music and cultural evolution.Journal of the Royal Society, Interface · 2024Article
- Understanding how personality traits, experiences, and attitudes shape negative bias toward AI-generated artworks.Scientific reports · 2024Article
- A transformers-based approach for fine and coarse-grained classification and generation of MIDI songs and soundtracks.PeerJ. Computer science · 2023Article
- AffectMachine-Classical: a novel system for generating affective classical music.Frontiers in psychology · 2023Article
- Am I (Deep) Blue? Music-Making AI and Emotional Awareness.Frontiers in neurorobotics · 2022Article
- Creativity in Generative Musical Networks: Evidence From Two Case Studies.Frontiers in robotics and AI · 2021Article
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Authors and funding
2 authors.
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Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.