Skip to content
#generative ai Open access

Narrative Music Theory as a Framework for Creative Ideation: From Harmonic Tension to Storyworld Structure

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)
Narrative Theory and Analysis

Abstract

This work develops a systematic framework that reinterprets core concepts of Western music theory as generative operators for narrative design. By treating harmonic tension, modal interchange, counterpoint, modulation, texture, rhythm, and atonality as abstract mechanisms that shape affect, causality, and world-building, the study demonstrates how musical structures can be translated into tools for constructing multi-layered and psychologically rich stories. The framework positions musical constructs—such as dissonance, deceptive cadences, reharmonization, polyrhythm, groove, ostinato, and minimal repetition—as narrative operators that model value conflict, temporal distortion, systemic pressure, thematic recurrence, and shifts in worldview. These operators are organized across three domains: character psychology, causal architecture, and storyworld structure, providing authors with a structured vocabulary for creative ideation. The paper situates this approach within recent scholarship on musical narrativity, including research on narrative space in post-minimal music, falsifying narration in minimalist process, and lexical narrative arcs in song lyrics. It further introduces concrete case studies illustrating how modal interchange and deceptive cadences can be applied to plot construction and character development. Appendices provide a glossary of musical-theoretical terms and foundational concepts in music theory, enabling readers without formal musical training to engage with the framework. Additional discussions address methodological limits, cognitive expectancy, cross-media applicability (film, interactive narrative, game design), and the potential integration of musical operators into AI-assisted story generation. Overall, the work proposes an interdisciplinary model in which music-theoretical structures function as a creative engine for narrative composition, offering both conceptual insight and practical tools for authors, researchers, and designers working across literary, audiovisual, and interactive media.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations

Related blog posts

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

GPT-Lab Oct 12, 2026

AI Has Grown Up. Have We?

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.