Interactive sonification strategies for the motion and emotion of dance performances

被引:8
|
作者
Landry, Steven [1 ]
Jeon, Myounghoon [1 ,2 ]
机构
[1] Michigan Technol Univ, Dept Cognit & Learning Sci, Houghton, MI 49931 USA
[2] Virginia Tech, Dept Ind & Syst Engn, Blacksburg, VA 24061 USA
关键词
Interactive sonification; Affective computing; Gesture; Musical interface; MUSIC PERFORMANCE; BODY MOVEMENT; COMMUNICATION; EXPRESSION; FEATURES; SPEECH; MODEL;
D O I
10.1007/s12193-020-00321-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sonification has the potential to communicate a variety of data types to listeners including not just cognitive information, but also emotions and aesthetics. The goal of our dancer sonification project is to "sonify emotions as well as motions" of a dance performance via musical sonification. To this end, we developed and evaluated sonification strategies for adding a layer of emotional mappings to data sonification. Experiment 1 developed and evaluated four musical sonifications (i.e., sin-ification, MIDI-fication, melody module, and melody and arrangement module) to see their emotional effects. Videos were recorded of a professional dancer interacting with each of the four musical sonification strategies. Forty-eight participants provided ratings of musicality, emotional expressivity, and sound-motion/emotion compatibility via an online survey. Results suggest that increasing musical mappings led to higher ratings for each dimension for dance-type gestures. Experiment 2 used the musical sonification framework to develop four sonification scenarios that aimed to communicate a target emotion (happy, sad, angry, and tender). Thirty participants compared four interactive sonification scenarios with four pre-composed dance choreographies featuring the same musical and gestural palettes. Both forced choice and multi-dimensional emotional evaluations were collected, as well as motion/emotion compatibility ratings. Results show that having both music and dance led to higher accuracy scores for most target emotions, compared to music or dance conditions alone. These findings can contribute to the fields of movement sonification, algorithmic music composition, as well as affective computing in general, by describing strategies for conveying emotion through sound.
引用
收藏
页码:167 / 186
页数:20
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