Personalized affective music player

Joris H. Janssen; Egon van den Broek; Joyce H.D.M. Westerink

doi:10.1109/ACII.2009.5349376

Personalized affective music player

Joris H. Janssen, Egon van den Broek, Joyce H.D.M. Westerink

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

19 Citations (Scopus)

118 Downloads (Pure)

Abstract

We introduce and test an affective music player (AMP) that selects music for mood enhancement. Through a concise overview of content, construct, and ecological validity, we elaborate five considerations that form the foundation of the AMP. Based on these considerations, computational models are developed, using regression and kernel density estimation. We show how these models can be used for music selection and how they can be extended to fit in other systems. Subsequently, the success of the models is illustrated with a user test. The AMP augments music listening, where its techniques, in general, enable automated affect guidance. Finally, we argue that our AMP is readily applicable to real-world situations as it can 1) cope with noisy situations, 2) handle the large inter-individual differences apparent in the musical domain, and 3) integrate context or other information, all in real-time.

Original language	English
Title of host publication	Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009
Editors	Jeffrey Cohn, Anton Nijholt, Maja Pantic
Place of Publication	Los Alamitos, NJ
Publisher	IEEE
Pages	472-477
Number of pages	6
Volume	1
ISBN (Print)	978-1-4244-4800-5
DOIs	https://doi.org/10.1109/ACII.2009.5349376
Publication status	Published - 10 Sept 2009
Event	3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009 - De Rode Hoed, Amsterdam, Netherlands Duration: 10 Sept 2009 → 12 Sept 2009 Conference number: 3

Conference

Conference	3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009
Abbreviated title	ACII
Country/Territory	Netherlands
City	Amsterdam
Period	10/09/09 → 12/09/09

Keywords

IR-73203
HMI-CI: Computational Intelligence
Models
MUSIC
Affective music player (AMP)
Context
Noisy situations
Emotion
Mood
EWI-18397
Psychophiology
Inter-individual differences
HMI-MI: MULTIMODAL INTERACTIONS
HMI-IE: Information Engineering
METIS-260075

Access to Document

10.1109/ACII.2009.5349376

Cite this

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title = "Personalized affective music player",

abstract = "We introduce and test an affective music player (AMP) that selects music for mood enhancement. Through a concise overview of content, construct, and ecological validity, we elaborate five considerations that form the foundation of the AMP. Based on these considerations, computational models are developed, using regression and kernel density estimation. We show how these models can be used for music selection and how they can be extended to fit in other systems. Subsequently, the success of the models is illustrated with a user test. The AMP augments music listening, where its techniques, in general, enable automated affect guidance. Finally, we argue that our AMP is readily applicable to real-world situations as it can 1) cope with noisy situations, 2) handle the large inter-individual differences apparent in the musical domain, and 3) integrate context or other information, all in real-time.",

keywords = "IR-73203, HMI-CI: Computational Intelligence, Models, MUSIC, Affective music player (AMP), Context, Noisy situations, Emotion, Mood, EWI-18397, Psychophiology, Inter-individual differences, HMI-MI: MULTIMODAL INTERACTIONS, HMI-IE: Information Engineering, METIS-260075",

author = "Janssen, \{Joris H.\} and \{van den Broek\}, Egon and Westerink, \{Joyce H.D.M.\}",

year = "2009",

month = sep,

day = "10",

doi = "10.1109/ACII.2009.5349376",

language = "English",

isbn = "978-1-4244-4800-5",

volume = "1",

pages = "472--477",

editor = "Jeffrey Cohn and Anton Nijholt and Maja Pantic",

booktitle = "Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009",

publisher = "IEEE",

address = "United States",

note = "3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009, ACII ; Conference date: 10-09-2009 Through 12-09-2009",

}

Janssen, JH, van den Broek, E & Westerink, JHDM 2009, Personalized affective music player. in J Cohn, A Nijholt & M Pantic (eds), Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. vol. 1, IEEE, Los Alamitos, NJ, pp. 472-477, 3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009, Amsterdam, Netherlands, 10/09/09. https://doi.org/10.1109/ACII.2009.5349376

Personalized affective music player. / Janssen, Joris H.; van den Broek, Egon; Westerink, Joyce H.D.M.
Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. ed. / Jeffrey Cohn; Anton Nijholt; Maja Pantic. Vol. 1 Los Alamitos, NJ: IEEE, 2009. p. 472-477.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Personalized affective music player

AU - Janssen, Joris H.

AU - van den Broek, Egon

AU - Westerink, Joyce H.D.M.

N1 - Conference code: 3

PY - 2009/9/10

Y1 - 2009/9/10

N2 - We introduce and test an affective music player (AMP) that selects music for mood enhancement. Through a concise overview of content, construct, and ecological validity, we elaborate five considerations that form the foundation of the AMP. Based on these considerations, computational models are developed, using regression and kernel density estimation. We show how these models can be used for music selection and how they can be extended to fit in other systems. Subsequently, the success of the models is illustrated with a user test. The AMP augments music listening, where its techniques, in general, enable automated affect guidance. Finally, we argue that our AMP is readily applicable to real-world situations as it can 1) cope with noisy situations, 2) handle the large inter-individual differences apparent in the musical domain, and 3) integrate context or other information, all in real-time.

AB - We introduce and test an affective music player (AMP) that selects music for mood enhancement. Through a concise overview of content, construct, and ecological validity, we elaborate five considerations that form the foundation of the AMP. Based on these considerations, computational models are developed, using regression and kernel density estimation. We show how these models can be used for music selection and how they can be extended to fit in other systems. Subsequently, the success of the models is illustrated with a user test. The AMP augments music listening, where its techniques, in general, enable automated affect guidance. Finally, we argue that our AMP is readily applicable to real-world situations as it can 1) cope with noisy situations, 2) handle the large inter-individual differences apparent in the musical domain, and 3) integrate context or other information, all in real-time.

KW - IR-73203

KW - HMI-CI: Computational Intelligence

KW - Models

KW - MUSIC

KW - Affective music player (AMP)

KW - Context

KW - Noisy situations

KW - Emotion

KW - Mood

KW - EWI-18397

KW - Psychophiology

KW - Inter-individual differences

KW - HMI-MI: MULTIMODAL INTERACTIONS

KW - HMI-IE: Information Engineering

KW - METIS-260075

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DO - 10.1109/ACII.2009.5349376

M3 - Conference contribution

SN - 978-1-4244-4800-5

VL - 1

SP - 472

EP - 477

BT - Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009

A2 - Cohn, Jeffrey

A2 - Nijholt, Anton

A2 - Pantic, Maja

PB - IEEE

CY - Los Alamitos, NJ

T2 - 3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009

Y2 - 10 September 2009 through 12 September 2009

ER -

Personalized affective music player

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