A self-report study that gauges perceived and induced emotion with music

D. Griffiths, Stuart Cunningham, Jonathan Weinel
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引用次数: 4

Abstract

This paper discusses a particular study that gauges emotion with respect to music by means of an online self-report survey. This is part of the ongoing construct of an intelligent mobile music player application that will adjudicate one's activity, environmental context, and physiological state. The study was structured so as to acquire emotional information by giving each participant a discrete affect word including `happy', `excited', `angry', `afraid', `miserable', `sad', `tired', and `relaxed'. Each affect word that was selected for a given song was corroborated by a degree of intensity using 5-point scale. The fundamental objective of this study was to measure as to how each song could be described emotionally, and how each song made them feel emotionally. Pearson's Chi-Squared concluded that 95% of the ratings for both `described' and `induced' emotions were statistically significant. The corresponding results were scaled to the proposed circular-based emotional model based on Russell's Circumplex model of emotion, by converting both the emotional ratings to polar coordinates. Further analysis of the data subsequently showed that the affect words that represent music could be given some granularity around the perimeter of the circle by expanding upon particular properties of Russell's circular ordering of affect words. Lastly, this paper concludes with a Section that outlines the future work for this research.
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一项自我报告研究,通过音乐来衡量感知和诱导的情感
本文讨论了一项特殊的研究,该研究通过在线自我报告调查来衡量情感与音乐的关系。这是智能移动音乐播放器应用程序正在构建的一部分,该应用程序将判断一个人的活动、环境背景和生理状态。这项研究的结构是通过给每个参与者一个独立的影响词来获取情感信息,包括“快乐”、“兴奋”、“生气”、“害怕”、“痛苦”、“悲伤”、“疲倦”和“放松”。为给定歌曲选择的每个影响词都用5分制的强度程度来证实。这项研究的基本目的是衡量每首歌是如何被情感描述的,以及每首歌是如何让他们感受到情感的。皮尔逊的Chi-Squared得出结论,95%的“描述”和“诱导”情绪的评分在统计上都是显著的。通过将两种情绪评级转换为极坐标,相应的结果被缩放到基于Russell's Circumplex情绪模型的圆形情绪模型中。随后对数据的进一步分析表明,通过扩展罗素影响词的循环排序的特定属性,可以在圆圈的周长周围赋予代表音乐的影响词一些粒度。最后,本文用一节概述了本研究的未来工作。
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