ITU

Mood Expression in Real-Time Computer Generated Music using Pure Data

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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Mood Expression in Real-Time Computer Generated Music using Pure Data. / Scirea, Marco; Nelson, Mark; Cheong, Yun-Gyung; Bae, Byung Chull.

Proceedings of the ICMPC-APSCOM 2014 Joint Conference. College of Music, Yonsei University, 2014. p. 263-267.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Scirea, M, Nelson, M, Cheong, Y-G & Bae, BC 2014, Mood Expression in Real-Time Computer Generated Music using Pure Data. in Proceedings of the ICMPC-APSCOM 2014 Joint Conference. College of Music, Yonsei University, pp. 263-267.

APA

Scirea, M., Nelson, M., Cheong, Y-G., & Bae, B. C. (2014). Mood Expression in Real-Time Computer Generated Music using Pure Data. In Proceedings of the ICMPC-APSCOM 2014 Joint Conference (pp. 263-267). College of Music, Yonsei University.

Vancouver

Scirea M, Nelson M, Cheong Y-G, Bae BC. Mood Expression in Real-Time Computer Generated Music using Pure Data. In Proceedings of the ICMPC-APSCOM 2014 Joint Conference. College of Music, Yonsei University. 2014. p. 263-267

Author

Scirea, Marco ; Nelson, Mark ; Cheong, Yun-Gyung ; Bae, Byung Chull. / Mood Expression in Real-Time Computer Generated Music using Pure Data. Proceedings of the ICMPC-APSCOM 2014 Joint Conference. College of Music, Yonsei University, 2014. pp. 263-267

Bibtex

@inproceedings{afd72706d1a24cad8a8bd2f8aae56cb6,
title = "Mood Expression in Real-Time Computer Generated Music using Pure Data",
abstract = "This paper presents an empirical study that investigated if procedurally generated music based on a set of musical features can elicit a target mood in the music listener. Drawn from the two-dimensional affect model proposed by Russell, the musical features that we have chosen to express moods are intensity, timbre, rhythm, and dissonances. The eight types of mood investigated in this study are being bored, content, happy, miserable, tired, fearful, peaceful, and alarmed. We created 8 short music clips using PD (Pure Data) programming language, each of them represents a particular mood. We carried out a pilot study and present a preliminary result.",
keywords = "music, mood, affective computing",
author = "Marco Scirea and Mark Nelson and Yun-Gyung Cheong and Bae, {Byung Chull}",
year = "2014",
month = aug
language = "English",
pages = "263--267",
booktitle = "Proceedings of the ICMPC-APSCOM 2014 Joint Conference",
publisher = " College of Music, Yonsei University",

}

RIS

TY - GEN

T1 - Mood Expression in Real-Time Computer Generated Music using Pure Data

AU - Scirea, Marco

AU - Nelson, Mark

AU - Cheong, Yun-Gyung

AU - Bae, Byung Chull

PY - 2014/8

Y1 - 2014/8

N2 - This paper presents an empirical study that investigated if procedurally generated music based on a set of musical features can elicit a target mood in the music listener. Drawn from the two-dimensional affect model proposed by Russell, the musical features that we have chosen to express moods are intensity, timbre, rhythm, and dissonances. The eight types of mood investigated in this study are being bored, content, happy, miserable, tired, fearful, peaceful, and alarmed. We created 8 short music clips using PD (Pure Data) programming language, each of them represents a particular mood. We carried out a pilot study and present a preliminary result.

AB - This paper presents an empirical study that investigated if procedurally generated music based on a set of musical features can elicit a target mood in the music listener. Drawn from the two-dimensional affect model proposed by Russell, the musical features that we have chosen to express moods are intensity, timbre, rhythm, and dissonances. The eight types of mood investigated in this study are being bored, content, happy, miserable, tired, fearful, peaceful, and alarmed. We created 8 short music clips using PD (Pure Data) programming language, each of them represents a particular mood. We carried out a pilot study and present a preliminary result.

KW - music

KW - mood

KW - affective computing

M3 - Article in proceedings

SP - 263

EP - 267

BT - Proceedings of the ICMPC-APSCOM 2014 Joint Conference

PB - College of Music, Yonsei University

ER -

ID: 80253435