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Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity

Amanda Rogers Orcid Logo, Matt Jones Orcid Logo, Alma Rahat, Ibukun Olatunji, Matt Sheppard

Conference: ICCC25 - 16th International Conference on Computational Creativity

Swansea University Authors: Amanda Rogers Orcid Logo, Matt Jones Orcid Logo, Alma Rahat

Abstract

We present a human-in-the-loop GAN framework for battle rap, where a human artist (MC) serves as generator, and the AI acts as an adaptive discriminator. The AI provides feedback on rhyme complexity, coherence, and stylistic alignment, challenging the MC’s improvisational skill. Fine-tuned language...

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Published in: Conference: ICCC25 - 16th International Conference on Computational Creativity
Published: 2025
Online Access: https://computationalcreativity.net/iccc25/papers/iccc25-olatunji2025battle.pdf
URI: https://cronfa.swan.ac.uk/Record/cronfa71550
first_indexed 2026-03-04T15:27:16Z
last_indexed 2026-03-04T15:27:16Z
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recordtype SURis
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spelling v2 71550 2026-03-04 Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity 5ddde1ecc99923098fd92c797ee0020b 0000-0002-0454-8183 Amanda Rogers Amanda Rogers true false 10b46d7843c2ba53d116ca2ed9abb56e 0000-0001-7657-7373 Matt Jones Matt Jones true false 6206f027aca1e3a5ff6b8cd224248bc2 Alma Rahat Alma Rahat true false 2026-03-04 BGPS We present a human-in-the-loop GAN framework for battle rap, where a human artist (MC) serves as generator, and the AI acts as an adaptive discriminator. The AI provides feedback on rhyme complexity, coherence, and stylistic alignment, challenging the MC’s improvisational skill. Fine-tuned language models emulate diverse rap styles, while voice cloning creates adversarial loops: the MC competesagainst stylised versions of their own voice in a dynamic, selfreflective duel. The system follows a dual-phase process: (i) an Emulation Phase, where AI mimics established flows to reinforce technical mastery, and (ii) an Improvisation Phase, where AI disrupts expectations to prompt originality. This ensures that creative growth emerges from constraint and challenge. Success is judged through MC evaluations of the AI’s performance as an adversary. Framed as a study paper, this work offers a thought experiment in adversarial co-creativity, modelling how AI might inspire, rather than merely assist, human expression. Beyond computational modelling, the framework offers insights into machine-mediated creativityand how AI can be designed to provoke human creativity through improvisation, challenge, and real-time performance. The study positions the AI as a dynamic co-performer capable of eliciting novel artistic responses. As such, it contributes to emerging discourse on creative AI systems that influence, not just assist, human expression Conference Paper/Proceeding/Abstract Conference: ICCC25 - 16th International Conference on Computational Creativity AI, creativity, rap 1 8 2025 2025-08-01 https://computationalcreativity.net/iccc25/papers/iccc25-olatunji2025battle.pdf COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University EPSRC studentship 2026-03-04T15:41:19.6670299 2026-03-04T15:18:30.2175171 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Geography Amanda Rogers 0000-0002-0454-8183 1 Matt Jones 0000-0001-7657-7373 2 Alma Rahat 3 Ibukun Olatunji 4 Matt Sheppard 5
title Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
spellingShingle Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
Amanda Rogers
Matt Jones
Alma Rahat
title_short Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
title_full Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
title_fullStr Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
title_full_unstemmed Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
title_sort Battle Rap as a Framework for Human-Machine Co-Creation. In Proceedings of the 16th International Conference on Computational Creativity
author_id_str_mv 5ddde1ecc99923098fd92c797ee0020b
10b46d7843c2ba53d116ca2ed9abb56e
6206f027aca1e3a5ff6b8cd224248bc2
author_id_fullname_str_mv 5ddde1ecc99923098fd92c797ee0020b_***_Amanda Rogers
10b46d7843c2ba53d116ca2ed9abb56e_***_Matt Jones
6206f027aca1e3a5ff6b8cd224248bc2_***_Alma Rahat
author Amanda Rogers
Matt Jones
Alma Rahat
author2 Amanda Rogers
Matt Jones
Alma Rahat
Ibukun Olatunji
Matt Sheppard
format Conference Paper/Proceeding/Abstract
container_title Conference: ICCC25 - 16th International Conference on Computational Creativity
publishDate 2025
institution Swansea University
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Geography{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Geography
url https://computationalcreativity.net/iccc25/papers/iccc25-olatunji2025battle.pdf
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description We present a human-in-the-loop GAN framework for battle rap, where a human artist (MC) serves as generator, and the AI acts as an adaptive discriminator. The AI provides feedback on rhyme complexity, coherence, and stylistic alignment, challenging the MC’s improvisational skill. Fine-tuned language models emulate diverse rap styles, while voice cloning creates adversarial loops: the MC competesagainst stylised versions of their own voice in a dynamic, selfreflective duel. The system follows a dual-phase process: (i) an Emulation Phase, where AI mimics established flows to reinforce technical mastery, and (ii) an Improvisation Phase, where AI disrupts expectations to prompt originality. This ensures that creative growth emerges from constraint and challenge. Success is judged through MC evaluations of the AI’s performance as an adversary. Framed as a study paper, this work offers a thought experiment in adversarial co-creativity, modelling how AI might inspire, rather than merely assist, human expression. Beyond computational modelling, the framework offers insights into machine-mediated creativityand how AI can be designed to provoke human creativity through improvisation, challenge, and real-time performance. The study positions the AI as a dynamic co-performer capable of eliciting novel artistic responses. As such, it contributes to emerging discourse on creative AI systems that influence, not just assist, human expression
published_date 2025-08-01T15:41:21Z
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score 11.453587

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