<div class="csl-bib-body">
<div class="csl-entry">Melchiorre, A. B., Penz, D., Ganhör, C., Lesota, O., Fragoso, V., Friztl, F., Parada-Cabaleiro, E., Schubert, F., & Schedl, M. (2022). EmoMTB: Emotion-aware Music Tower Blocks. In <i>ICMR ’22: Proceedings of the 2022 International Conference on Multimedia Retrieval</i> (pp. 206–210). https://doi.org/10.1145/3512527.3531351</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/139845
-
dc.description.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.
en
dc.language.iso
en
-
dc.subject
clustering
en
dc.subject
emotion recognition
en
dc.subject
intelligent user interface
en
dc.subject
music exploration
en
dc.title
EmoMTB: Emotion-aware Music Tower Blocks
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Johannes Kepler University of Linz, Austria
-
dc.contributor.affiliation
Johannes Kepler University of Linz, Austria
-
dc.contributor.affiliation
Johannes Kepler University of Linz, Austria
-
dc.contributor.affiliation
Salzburg University of Applied Sciences, Austria
-
dc.contributor.affiliation
Johannes Kepler University of Linz, Austria
-
dc.contributor.affiliation
University of Applied Arts Vienna, Austria
-
dc.description.startpage
206
-
dc.description.endpage
210
-
dc.type.category
Full-Paper Contribution
-
tuw.booktitle
ICMR '22: Proceedings of the 2022 International Conference on Multimedia Retrieval
-
tuw.peerreviewed
true
-
tuw.researchTopic.id
I4a
-
tuw.researchTopic.name
Information Systems Engineering
-
tuw.researchTopic.value
100
-
tuw.publication.orgunit
E194-06 - Forschungsbereich Machine Learning
-
tuw.publisher.doi
10.1145/3512527.3531351
-
dc.description.numberOfPages
5
-
tuw.author.orcid
0000-0003-1643-1166
-
tuw.author.orcid
0000-0003-1850-2626
-
tuw.author.orcid
0000-0002-8321-6565
-
tuw.author.orcid
0000-0003-1843-3632
-
tuw.event.name
ACM International Conference on Multimedia Retrieval
en
tuw.event.startdate
27-06-2022
-
tuw.event.enddate
30-06-2022
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.country
US
-
tuw.event.presenter
Melchiorre, Alessandro Benedetto
-
wb.sciencebranch
Informatik
-
wb.sciencebranch.oefos
1020
-
wb.sciencebranch.value
100
-
item.openairetype
conference paper
-
item.languageiso639-1
en
-
item.cerifentitytype
Publications
-
item.fulltext
no Fulltext
-
item.grantfulltext
none
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
crisitem.author.dept
Johannes Kepler University of Linz
-
crisitem.author.dept
E194-06 - Forschungsbereich Machine Learning
-
crisitem.author.dept
Johannes Kepler University of Linz
-
crisitem.author.dept
Johannes Kepler University of Linz
-
crisitem.author.dept
Salzburg University of Applied Sciences
-
crisitem.author.dept
Johannes Kepler University of Linz
-
crisitem.author.dept
University of Applied Arts Vienna
-
crisitem.author.dept
E185 - Institut für Computersprachen
-
crisitem.author.orcid
0000-0003-1643-1166
-
crisitem.author.orcid
0000-0003-1850-2626
-
crisitem.author.orcid
0000-0002-8321-6565
-
crisitem.author.orcid
0000-0003-1843-3632
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
