Dancing Guide: Near Realtime Audio Classification of Live Dance Music on Smartphones

Alexander Seewald

Abstract

Between 2008 and 2014 we developed and deployed a live music classification system, Dancing Guide, to be run on Android and iPhones mobile phones in near realtime. Although internet access was needed to send feedback and classifications to the server for statistical purposes, the music classification system also worked offline without any loss in accuracy or speed. This is essential since in most discos and dancing schools, internet access is spotty at best. During the seven years of the project, the app was available both for iPhone and Android, initially in German and English, but later – thanks to volunteer translations – also in Czech, Spanish, French, Italian, Japanese, Korean, Dutch, Polish, Portuguese, Russian and Traditional Chinese. Measured by user feedback, we achieved an accuracy of roughly 73% at a coverage of 61%. While the accuracy is comparable to initial estimates using cross-validation, the coverage is much worse. Background noise – which we did not model – or the limited feature set may have been responsible. We retrained the system several times, however performance did not always improve, so we sometimes left the previously trained system in place. In the end, the limited feature set which was initially chosen prevented further improvement of coverage and accuracy, and we stopped further development.

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Paper Citation


in Harvard Style

Seewald A. (2021). Dancing Guide: Near Realtime Audio Classification of Live Dance Music on Smartphones.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 891-898. DOI: 10.5220/0010258508910898


in Bibtex Style

@conference{icaart21,
author={Alexander Seewald},
title={Dancing Guide: Near Realtime Audio Classification of Live Dance Music on Smartphones},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={891-898},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010258508910898},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Dancing Guide: Near Realtime Audio Classification of Live Dance Music on Smartphones
SN - 978-989-758-484-8
AU - Seewald A.
PY - 2021
SP - 891
EP - 898
DO - 10.5220/0010258508910898