Auris: creating affective virtual spaces from music

VRST(2017)

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摘要
Affective virtual spaces are of interest in many virtual reality applications such as education, wellbeing, rehabilitation, and entertainment. In this paper we present Auris, a system that attempts to generate affective virtual environments from music. We use music as input because it inherently encodes emotions that listeners readily recognize and respond to. Creating virtual environments is a time consuming and labor-intensive task involving various skills like design, 3D modeling, texturing, animation, and coding. Auris helps make this easier by automating the virtual world generation task using mood and content extracted from song audio and lyrics data respectively. Our user study results indicate virtual spaces created by Auris successfully convey the mood of the songs used to create them and achieve high presence scores with the potential to provide novel experiences of listening to music.
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关键词
Virtual Reality, Music, Deep Neural Networks, Generative Models
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