On the Interrelation Between Listener Characteristics and the Perception of Emotions in Classical Orchestra Music
This study deals with the strong relationship between emotions and music, investigating three main research questions: (RQ1) Are there differences in human music perception (e.g., emotions, tempo, instrumentation, and complexity), according to musical education, experience, demographics, and persona...
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Published in | IEEE transactions on affective computing Vol. 9; no. 4; pp. 507 - 525 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Piscataway
IEEE
01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | This study deals with the strong relationship between emotions and music, investigating three main research questions: (RQ1) Are there differences in human music perception (e.g., emotions, tempo, instrumentation, and complexity), according to musical education, experience, demographics, and personality traits?; (RQ2) Do certain perceived music characteristics correlate (e.g., tension and sadness), irrespective of a particular listener's background or personality?; (RQ3) Does human perception of music characteristics, such as emotions and tempo, correlate with descriptors extracted from music audio signals? To investigate our research questions, we conducted two user studies focusing on different groups of subjects. We used web-based surveys to collect information about demographics, listening habits, musical education, personality, and perceptual ratings with respect to perceived emotions, tempo, complexity, and instrumentation for 15 segments of Beethoven's 3 rd symphony, "Eroica". Our experiments showed that all three research questions can be affirmed, at least partly. We found strong support for RQ2 and RQ3, while RQ1 could be confirmed only for some perceptual aspects and user groups. |
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AbstractList | This study deals with the strong relationship between emotions and music, investigating three main research questions: (RQ1) Are there differences in human music perception (e.g., emotions, tempo, instrumentation, and complexity), according to musical education, experience, demographics, and personality traits?; (RQ2) Do certain perceived music characteristics correlate (e.g., tension and sadness), irrespective of a particular listener's background or personality? (RQ3) Does human perception of music characteristics, such as emotions and tempo, correlate with descriptors extracted from music audio signals? To investigate our research questions, we conducted two user studies focusing on different groups of subjects. We used web-based surveys to collect information about demographics, listening habits, musical education, personality, and perceptual ratings with respect to perceived emotions, tempo, complexity, and instrumentation for 15 segments of Beethoven's 3rd symphony, “Eroic”. Our experiments showed that all three research questions can be affirmed, at least partly. We found strong support for RQ2 and RQ3, while RQ1 could be confirmed only for some perceptual aspects and user groups. This study deals with the strong relationship between emotions and music, investigating three main research questions: (RQ1) Are there differences in human music perception (e.g., emotions, tempo, instrumentation, and complexity), according to musical education, experience, demographics, and personality traits?; (RQ2) Do certain perceived music characteristics correlate (e.g., tension and sadness), irrespective of a particular listener's background or personality?; (RQ3) Does human perception of music characteristics, such as emotions and tempo, correlate with descriptors extracted from music audio signals? To investigate our research questions, we conducted two user studies focusing on different groups of subjects. We used web-based surveys to collect information about demographics, listening habits, musical education, personality, and perceptual ratings with respect to perceived emotions, tempo, complexity, and instrumentation for 15 segments of Beethoven's 3 rd symphony, "Eroica". Our experiments showed that all three research questions can be affirmed, at least partly. We found strong support for RQ2 and RQ3, while RQ1 could be confirmed only for some perceptual aspects and user groups. |
Author | Schedl, Markus Martorell, Agustin Tkalcic, Marko Eghbal-Zadeh, Hamid Trent, Erika S. Gomez, Emilia |
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References | ref13 ref56 ref59 ref15 ref58 ref14 ref11 ref54 ref10 ref17 ref16 ref19 ref18 sloboda (ref3) 2001 kosinski (ref46) 2013; 110 eerola (ref22) 2009 schmidt (ref27) 2009 ref51 ref50 song (ref28) 2012 ref45 ref48 ref47 ekman (ref6) 1972 ref41 ref44 laurier (ref5) 2011 hu (ref33) 2010 ref7 ref9 ref4 kim (ref31) 2010 ferwerda (ref40) 2015 li (ref30) 2003 tkal?i? (ref42) 2015 laurier (ref34) 2009 krippendorff (ref57) 2013 ref37 ref36 hu (ref32) 2008 ref2 ref1 ref39 ref38 bogdanov (ref53) 2014; 6 hu (ref35) 2009 hu (ref25) 2009 skowron (ref49) 2016 juslin (ref8) 2001 ref24 ref23 ref26 ref20 john (ref43) 1999; 2 ref21 laurier (ref12) 2009 ekman (ref55) 1999 liu (ref29) 2003 zenter (ref52) 2008; 8 |
References_xml | – ident: ref9 doi: 10.2466/pms.2003.96.3c.1117 – year: 1972 ident: ref6 publication-title: Emotion in the human face Guidelines for research and an integration of findings – ident: ref41 doi: 10.1145/2702613.2732754 – year: 2003 ident: ref30 article-title: Detecting emotion in music – year: 2009 ident: ref27 article-title: Projection of acoustic features to continuous valence-arousal mood labels via regression – ident: ref19 doi: 10.1016/j.cub.2009.02.058 – ident: ref36 doi: 10.1111/j.1467-6494.1992.tb00970.x – ident: ref50 doi: 10.1109/T-AFFC.2012.5 – start-page: 364 year: 2015 ident: ref42 article-title: Personality correlates for digital concert program notes publication-title: Proc Int Conf User Modeling Adaptation and Personalization – ident: ref39 doi: 10.1348/000712606X111177 – ident: ref13 doi: 10.1093/cercor/bhr353 – ident: ref20 doi: 10.1201/b10731 – start-page: 107 year: 2016 ident: ref49 article-title: Fusing social media cues: Personality prediction from Twitter and Instagram publication-title: Proc 25th Int Conf Companion World Wide Web doi: 10.1145/2872518.2889368 – year: 2013 ident: ref57 publication-title: Content Analysis An Introduction to Its Methodology – ident: ref17 doi: 10.1109/TAFFC.2014.2343222 – ident: ref26 doi: 10.1109/ICMLA.2008.96 – year: 2009 ident: ref35 article-title: Lyric-based song emotion detection with affective lexicon and fuzzy clustering method – ident: ref47 doi: 10.1109/PASSAT/SocialCom.2011.26 – year: 2012 ident: ref28 article-title: Evaluation of musical features for emotion classification – ident: ref45 doi: 10.1109/TAFFC.2014.2330816 – year: 2010 ident: ref33 article-title: When lyrics outperform audio for music mood classification: A feature analysis – year: 2008 ident: ref32 article-title: The 2007 MIREX audio mood classification task: Lessons learned – ident: ref24 doi: 10.1080/09298215.2010.513733 – ident: ref7 doi: 10.1080/0929821042000317813 – ident: ref4 doi: 10.1348/000712610X506831 – ident: ref44 doi: 10.1016/j.jrp.2005.08.007 – ident: ref51 doi: 10.1007/s11257-016-9173-y – year: 2009 ident: ref25 article-title: Lyric text mining in music mood classification – year: 2011 ident: ref5 article-title: Automatic classification of music mood by content-based analysis – ident: ref23 doi: 10.1109/TASL.2010.2064164 – ident: ref18 doi: 10.2307/40285811 – ident: ref56 doi: 10.1511/2001.4.344 – start-page: 71 year: 2001 ident: ref8 publication-title: Psychological Perspectives on Music and Emotion – start-page: 9 year: 2009 ident: ref34 publication-title: Automatic Detection of Emotion in Music Interaction with Emotionally Sensitive Machines – ident: ref59 doi: 10.1057/jt.2009.5 – ident: ref54 doi: 10.1016/S0092-6566(03)00046-1 – volume: 6 start-page: 855 year: 2014 ident: ref53 article-title: Essentia: An open source library for audio analysis publication-title: ACM SIGMM Records – ident: ref48 doi: 10.1007/s11257-016-9171-0 – ident: ref1 doi: 10.1037/h0054832 – volume: 110 start-page: 5802 year: 2013 ident: ref46 article-title: Private traits and attributes are predictable from digital records of human behavior publication-title: Proc Natl Acad Sci United States America doi: 10.1073/pnas.1218772110 – volume: 8 year: 2008 ident: ref52 article-title: Emotions evoked by the sound of music: Characterization, classification, and measurement publication-title: Emotion – year: 2001 ident: ref3 publication-title: Music and Emotion Theory and Research – year: 2009 ident: ref12 article-title: Music mood representation from social tags – ident: ref37 doi: 10.1037/0022-3514.84.6.1236 – ident: ref16 doi: 10.1037/a0022406 – ident: ref11 doi: 10.1037/h0077714 – year: 2010 ident: ref31 article-title: Music emotion recognition: A state of the art review – year: 2009 ident: ref22 article-title: Prediction of multidimensional emotional ratings in music from audio using multivariate regression models – year: 2015 ident: ref40 article-title: Personality & emotional states: Understanding users music listening needs publication-title: UMAP Extended Proc – ident: ref10 doi: 10.1037/1528-3542.8.4.494 – ident: ref2 doi: 10.2307/3344092 – year: 2003 ident: ref29 article-title: Automatic mood detection from acoustic music data – ident: ref58 doi: 10.2307/2529310 – ident: ref21 doi: 10.1145/2168752.2168754 – ident: ref38 doi: 10.1177/0305735607070382 – start-page: 45 year: 1999 ident: ref55 publication-title: Basic Emotions – ident: ref14 doi: 10.1037/0022-3514.60.1.37 – volume: 2 start-page: 102 year: 1999 ident: ref43 article-title: The Big Five trait taxonomy: History, measurement, and theoretical perspectives publication-title: Handbook of Personality Theory and Research – ident: ref15 doi: 10.1177/0305735610362821 |
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SubjectTerms | agreement and correlation in music perception audio analysis Audio signals classical music Complexity Complexity theory Demographics Education Emotion perception in music Emotion recognition Emotions Feature extraction Instruments Mood Multiple signal classification Music Perception Perceptions Personality User groups user study |
Title | On the Interrelation Between Listener Characteristics and the Perception of Emotions in Classical Orchestra Music |
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