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Modeling Affective Responses to Music Using Audio Signal Analysis and Physiology

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Book cover Music, Mind, and Embodiment (CMMR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9617))

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Abstract

A key issue in designing personalized music affective applications is to find effective ways to direct emotion by music selection with appropriate combination of acoustic features. The aim of this study is to understand the dynamic relationships between acoustic features, physiology and affective states. To model these relationships we used a multivariate approach including continuous measures of emotions from behavioral, subjective and physiological responses. Classical music excerpts taken from opera overtures were used as stimuli to induce emotional variations across time between neutral and intense emotional states. Continuous ratings of arousal and valence along with cardiovascular, respiratory, skin conductance and facial expressive activity were recorded simultaneously. Results show that parts of the music with higher loudness and pulse clarity induced higher ratings of arousal, sympathetic activation and increased cardiorespiratory synchronization. In contrast, pleasant and calming parts with major mode and prominent key strength induced higher ratings of valence, parasympathetic activation and increased facial activity.

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Acknowledgments

This work is supported by the SUTD-MIT International design center (IDC) Research Grant (IDG31200107/IDD11200105/IDD61200103). The authors thank Hải Lê Vũ for valuable technical assistance during the experiments.

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Authors and Affiliations

  1. Department of Information Systems Technology and Design, Singapore University of Technology and Design, 8 Somapah Road, Building 1, Level 5, Singapore, 487372, Singapore

    Konstantinos Trochidis & Simon Lui

Authors
  1. Konstantinos Trochidis
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  2. Simon Lui
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Correspondence to Konstantinos Trochidis .

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Editors and Affiliations

  1. CNRS - LMA, Marseille Cedex 20, France

    Richard Kronland-Martinet

  2. CNRS - LMA, Marseille, France

    Mitsuko Aramaki

  3. CNRS - LMA, Marseille, France

    Sølvi Ystad

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Trochidis, K., Lui, S. (2016). Modeling Affective Responses to Music Using Audio Signal Analysis and Physiology. In: Kronland-Martinet, R., Aramaki, M., Ystad, S. (eds) Music, Mind, and Embodiment. CMMR 2015. Lecture Notes in Computer Science(), vol 9617. Springer, Cham. https://doi.org/10.1007/978-3-319-46282-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-46282-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46281-3

  • Online ISBN: 978-3-319-46282-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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