RapViz: Rhyme Detection and Visualization of Rap Music

Paul Müller, Paul Müller, Lukas Panzer, Fabian Beck

2025

Abstract

RapViz transforms lyrics and audio of rap music into interactive visualizations, highlighting assonance rhymes and rhyme schemes. To accomplish this task, we have built a custom rhyme detector and extract respective timestamps from the audio file. The visualization integrates dynamic, time-based components to present insights from the rhyme analysis. Two linked views provide textual and temporal perspectives on a song. They can be viewed as an animation while the song plays and explored interactively afterwards. We demonstrate how our approach helps analyzing different songs covering different styles of rap.

Paper Citation

in Harvard Style

Müller P., Panzer L. and Beck F. (2025). RapViz: Rhyme Detection and Visualization of Rap Music. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP; ISBN 978-989-758-728-3, SciTePress, pages 730-739. DOI: 10.5220/0013190700003912

in Bibtex Style

@conference{ivapp25,
author={Paul Müller and Lukas Panzer and Fabian Beck},
title={RapViz: Rhyme Detection and Visualization of Rap Music},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP},
year={2025},
pages={730-739},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013190700003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP
TI - RapViz: Rhyme Detection and Visualization of Rap Music
SN - 978-989-758-728-3
AU - Müller P.
AU - Panzer L.
AU - Beck F.
PY - 2025
SP - 730
EP - 739
DO - 10.5220/0013190700003912
PB - SciTePress