AI-Based Affective Music Generation Systems: A Review of Methods, and Challenges
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Abstract (arXiv)
Music is a powerful medium for altering the emotional state of the listener. In recent years, with significant advancement in computing capabilities, artificial intelligence-based (AI-based) approaches have become popular for creating affective music generation (AMG) systems that are empowered with the ability to generate affective music. Entertainment, healthcare, and sensor-integrated interactive system design are a few of the areas in which AI-based affective music generation (AI-AMG) systems may have a significant impact. Given the surge of interest in this topic, this article aims to provide a comprehensive review of AI-AMG systems. The main building blocks of an AI-AMG system are discussed, and existing systems are formally categorized based on the core algorithm used for music generation. In addition, this article discusses the main musical features employed to compose affective music, along with the respective AI-based approaches used for tailoring them. Lastly, the main challenges and open questions in this field, as well as their potential solutions, are presented to guide future research. We hope that this review will be useful for readers seeking to understand the state-of-the-art in AI-AMG systems, and gain an overview of the methods used for developing them, thereby helping them explore this field in the future.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 18 of its 119 references that are in the map. First posted on arXiv 10 Jan 2023.
Builds on
18 of 119 references.
References · 18
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6 more
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Built on by
Citing papers per year: 2023: 1; 2024: 1; 2025: 6; 2026: 1.
9 papers.
- 2024Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding Challengescited by 7
- 2025A Comprehensive Survey on Generative AI for Video-to-Music Generationcited by 4
- 2025A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectivescited by 4
- 2025SyMuPe: Affective and Controllable Symbolic Music Performancecited by 3
- 2023AffectMachine-Classical: A novel system for generating affective classical musiccited by 1
- 2025Once Upon an AI: Six Scaffolds for Child-AI Interaction Design, Inspired by Disneycited by 0
- 2025TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantizationcited by 0
- 2025Story2MIDI: Emotionally Aligned Music Generation from Textcited by 0
- 2026AI-Based Sound Effect Generation: A Narrative Review of Generative Models Across Input Modalitiescited by 0
- 2026AI-Based Sound Effect Generation: A Narrative Review of Generative Models Across Input Modalities4 Aug 2026
- 2025Story2MIDI: Emotionally Aligned Music Generation from Text1 Dec 2025
- 2025SyMuPe: Affective and Controllable Symbolic Music Performance5 Nov 2025
- 2025TinyMusician: On-Device Music Generation with Knowledge Distillation and Mixed Precision Quantization31 Aug 2025
- 2025Once Upon an AI: Six Scaffolds for Child-AI Interaction Design, Inspired by Disney11 Apr 2025
- 2025A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectives1 Apr 2025
- 2025A Comprehensive Survey on Generative AI for Video-to-Music Generation18 Feb 2025
- 2024Are We There Yet? A Brief Survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges13 Jun 2024
- 2023AffectMachine-Classical: A novel system for generating affective classical music11 Apr 2023