By the same authors

Predicting GEMS Based on PDA-Assessed Gestural Motion Data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Predicting GEMS Based on PDA-Assessed Gestural Motion Data. / Irrgang, Melanie; Egermann, Hauke; Acar, Esra; Lommatzsch, Andreas.

Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment. ed. / Richard Kronland-Martinet; Mitsuko Aramaki; Sølvi Ystad; Joel Eaton. Interdisciplinary Centre for Computer Music Research, 2015. p. 472-485.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Irrgang, M, Egermann, H, Acar, E & Lommatzsch, A 2015, Predicting GEMS Based on PDA-Assessed Gestural Motion Data. in R Kronland-Martinet, M Aramaki, S Ystad & J Eaton (eds), Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment. Interdisciplinary Centre for Computer Music Research, pp. 472-485.

APA

Irrgang, M., Egermann, H., Acar, E., & Lommatzsch, A. (2015). Predicting GEMS Based on PDA-Assessed Gestural Motion Data. In R. Kronland-Martinet, M. Aramaki, S. Ystad, & J. Eaton (Eds.), Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment (pp. 472-485). Interdisciplinary Centre for Computer Music Research.

Vancouver

Irrgang M, Egermann H, Acar E, Lommatzsch A. Predicting GEMS Based on PDA-Assessed Gestural Motion Data. In Kronland-Martinet R, Aramaki M, Ystad S, Eaton J, editors, Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment. Interdisciplinary Centre for Computer Music Research. 2015. p. 472-485

Author

Irrgang, Melanie ; Egermann, Hauke ; Acar, Esra ; Lommatzsch, Andreas. / Predicting GEMS Based on PDA-Assessed Gestural Motion Data. Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment. editor / Richard Kronland-Martinet ; Mitsuko Aramaki ; Sølvi Ystad ; Joel Eaton. Interdisciplinary Centre for Computer Music Research, 2015. pp. 472-485

Bibtex - Download

@inproceedings{c633a465a73c481c9067361f55828a08,
title = "Predicting GEMS Based on PDA-Assessed Gestural Motion Data",
abstract = "Music is often discussed to be perceived as emotional because it renders expressive movements into audible musical structures. Thus, a valid approach to measure musical emotion could be to assess movement stimulated by music. This study evaluated the discriminative power of mobile-device generated acceleration data produced by free movement during music listening experience for the prediction of different degrees of the Geneva Emotion Music Scales (GEMS-9). The variance of the perceived GEMS-states can be explained by the fitted models as follows: power (r2 = .36), sadness (r2 = .17), tenderness (r2 = .14), joy (r2 = .15), tension (r2 = .11), peacefulness (r2 = .08), nostalgia (r2 = .07), wonder (r2 = .07) and transcendence (r2 = .02). These findings will contribute to understand, how acceleration data can be used to integrate embodied music cognition into Music Recommender Systems.",
keywords = "embodiment,emotion,gems,music information retrieval,music recommender systems",
author = "Melanie Irrgang and Hauke Egermann and Esra Acar and Andreas Lommatzsch",
year = "2015",
language = "Undefined/Unknown",
pages = "472--485",
editor = "Richard Kronland-Martinet and Mitsuko Aramaki and S{\o}lvi Ystad and Joel Eaton",
booktitle = "Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment",
publisher = "Interdisciplinary Centre for Computer Music Research",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Predicting GEMS Based on PDA-Assessed Gestural Motion Data

AU - Irrgang, Melanie

AU - Egermann, Hauke

AU - Acar, Esra

AU - Lommatzsch, Andreas

PY - 2015

Y1 - 2015

N2 - Music is often discussed to be perceived as emotional because it renders expressive movements into audible musical structures. Thus, a valid approach to measure musical emotion could be to assess movement stimulated by music. This study evaluated the discriminative power of mobile-device generated acceleration data produced by free movement during music listening experience for the prediction of different degrees of the Geneva Emotion Music Scales (GEMS-9). The variance of the perceived GEMS-states can be explained by the fitted models as follows: power (r2 = .36), sadness (r2 = .17), tenderness (r2 = .14), joy (r2 = .15), tension (r2 = .11), peacefulness (r2 = .08), nostalgia (r2 = .07), wonder (r2 = .07) and transcendence (r2 = .02). These findings will contribute to understand, how acceleration data can be used to integrate embodied music cognition into Music Recommender Systems.

AB - Music is often discussed to be perceived as emotional because it renders expressive movements into audible musical structures. Thus, a valid approach to measure musical emotion could be to assess movement stimulated by music. This study evaluated the discriminative power of mobile-device generated acceleration data produced by free movement during music listening experience for the prediction of different degrees of the Geneva Emotion Music Scales (GEMS-9). The variance of the perceived GEMS-states can be explained by the fitted models as follows: power (r2 = .36), sadness (r2 = .17), tenderness (r2 = .14), joy (r2 = .15), tension (r2 = .11), peacefulness (r2 = .08), nostalgia (r2 = .07), wonder (r2 = .07) and transcendence (r2 = .02). These findings will contribute to understand, how acceleration data can be used to integrate embodied music cognition into Music Recommender Systems.

KW - embodiment,emotion,gems,music information retrieval,music recommender systems

M3 - Conference contribution

SP - 472

EP - 485

BT - Proceedings of the 11th International Symposium on Computer Music Multidisciplinary Research (CMMR) Music, Mind, and Embodiment

A2 - Kronland-Martinet, Richard

A2 - Aramaki, Mitsuko

A2 - Ystad, Sølvi

A2 - Eaton, Joel

PB - Interdisciplinary Centre for Computer Music Research

ER -