Abstract
We introduce Emotion-aware Music Tower Blocks (EmoMTB), an audiovisual interface to explore large music collections. It creates a musical landscape, by adopting the metaphor of a city, where similar songs are grouped into the same building and nearby buildings form neighborhoods of particular genres. In order to personalize the user experience, an underlying classifier monitors textual user-generated content, by predicting their emotional state and adapting the audiovisual elements of the interface accordingly. EmoMTB enables users to explore different musical styles either within their comfort zone or outside of it. Besides, tailoring the results of the recommender engine to match the affective state of the user, EmoMTB offers a unique way to discover and enjoy music. EmoMTB supports exploring a collection of circa half a million streamed songs using a regular smartphone as a control interface to navigate in the landscape.
Citation
Alessandro B.
Melchiorre,
David
Penz,
Christian
Ganhör,
Oleg
Lesota,
Vasco Bezold Rosner
Fragoso,
Florian Friztl,
Emilia
Parada-Cabaleiro,
Franz Schubert,
Markus
Schedl
EmoMTB: Emotion-aware Music Tower Blocks
Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR),
206--210, doi:10.1145/3512527.3531351, 2022.
BibTeX
@article{Melchiorre2022EMOMTB,
title = {EmoMTB: Emotion-aware Music Tower Blocks},
author = {Melchiorre, Alessandro B. and Penz, David and Ganhör, Christian and Lesota, Oleg and Fragoso, Vasco Bezold Rosner and Friztl, Florian and Parada-Cabaleiro, Emilia and Schubert, Franz and Schedl, Markus},
booktitle = {Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR)},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
doi = {10.1145/3512527.3531351},
url = {https://doi.org/10.1145/3512527.3531351},
pages = {206--210},
location = {Newark, NJ, USA},
year = {2022}
}