AI Methods in Algorithmic Composition: A Comprehensive Survey
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Abstract (arXiv)
Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Feb 2014.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 2; 2024: 3; 2025: 3; 2026: 1.
12 papers.
- 2021A Quantum Natural Language Processing Approach to Musical Intelligencecited by 11
- 2024Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Surveycited by 10
- 2025Survey on the Evaluation of Generative Models in Musiccited by 10
- 2024A Survey of Deep Learning Audio Generation Methodscited by 5
- 2023IteraTTA: An interface for exploring both text prompts and audio priors in generating music with text-to-audio modelscited by 3
- 2023The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experimentcited by 1
- 2021The artificial synesthete: Image-melody translations with variational autoencoderscited by 0
- 2022Open Challenges in Musical Metacreationcited by 0
- 2024MuseBarControl: Enhancing Fine-Grained Control in Symbolic Music Generation through Pre-Training and Counterfactual Losscited by 0
- 2025Expressive Music Data Processing and Generationcited by 0
- 2025Apollo: An Interactive Environment for Generating Symbolic Musical Phrases using Corpus-based Style Imitationcited by 0
- 2026From local kernels to global form: modeling the emergence of musical contentcited by 0
- 2026From local kernels to global form: modeling the emergence of musical content25 Aug 2026
- 2025Survey on the Evaluation of Generative Models in Music5 Jun 2025
- 2025Apollo: An Interactive Environment for Generating Symbolic Musical Phrases using Corpus-based Style Imitation18 Apr 2025
- 2025Expressive Music Data Processing and Generation14 Mar 2025
- 2024MuseBarControl: Enhancing Fine-Grained Control in Symbolic Music Generation through Pre-Training and Counterfactual Loss5 Jul 2024
- 2024A Survey of Deep Learning Audio Generation Methods31 May 2024
- 2024Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey27 Feb 2024
- 2023The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experiment13 Nov 2023
- 2023IteraTTA: An interface for exploring both text prompts and audio priors in generating music with text-to-audio models24 Jul 2023
- 2022Open Challenges in Musical Metacreation31 Aug 2022
- 2021The artificial synesthete: Image-melody translations with variational autoencoders6 Dec 2021
- 2021A Quantum Natural Language Processing Approach to Musical Intelligence10 Nov 2021