基于脑电的虚拟现实诱发下情绪状态分类
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作者单位:

1.南京航空航天大学艺术学院,南京211106;2.南京航空航天大学计算机科学与技术学院,南京211106

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国家重点研发计划(2018YFC2001600, 2018YFC2001602)资助项目;国家自然科学基金(61876082)资助项目;江苏省高等教育教改课题(2021JSJG361)资助项目。


Emotion Classification Induced by Virtual Reality Based on EEG
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Affiliation:

1.College of Art, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China;2.College of Computer Science and Technology, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China

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    摘要:

    情绪在歌唱活动中发挥着重要作用,但现阶段高校声乐课程缺乏对情绪调动的有效训练。由于虚拟现实技术具有真实性、沉浸性的特征,本文提出将其应用于声乐教学过程中的情绪诱发阶段。为了验证虚拟现实技术对情绪诱发的有效性,本文提取了不同类型的脑电特征,对情绪自我想象和虚拟现实情绪诱发两种场景下的情绪状态进行分类,并对比了情绪分类准确率、情绪自评分数和声乐自评分数,从主观和客观两方面探究虚拟现实技术对参与者情绪调动的影响。实验结果表明,相比于传统自我想象,虚拟现实技术可以极大地诱发参与者情绪,提升演唱效果,从而为声乐演唱教学提供一种新的辅助手段。

    Abstract:

    Emotion plays an important role in singing. At present, vocal music courses in universities lack effective training for emotion mobilization. Due to the authenticity and immersive of virtual reality (VR) technology, this article applies it to the emotional induction stage in vocal music teaching. To verify the effectiveness of VR technology for emotion induction, different types of electroencephalogram (EEG) features are extracted, and then emotions are classified into two scenarios: emotional self-imagination and VR-induced. The accuracy of emotion classification, self-evaluation score of emotion and self-evaluation score of vocal music are compared to explore the influence of VR on participants’ emotion mobilization from both subjective and objective aspects. Experimental results show that compared with traditional self-imagination, VR technology can greatly induce the emotions of participants and enhance the singing performance, thus providing a new auxiliary method for vocal singing teaching.

    表 2 SAM量表平均分数和显著性检验结果Table 2 Average scores and significance test results of SAM
    表 5 特征选择中出现次数大于950次的特征Table 5 Features with more than 950 occurrences in feature selection
    表 4 情绪识别分类准确率Table 4 Accuracy of emotion recognition classification
    表 3 声乐自评量表平均分数和显著性检验结果Table 3 Average score and significance test result of vocal self-rating scale
    图1 实验流程图Fig.1 Flow chart of experiment
    图2 实验范式Fig.2 Experimental paradigm
    图3 6首歌曲虚拟现实全景视频画面Fig.3 Virtual reality panoramic video pictures of six songs
    图4 情绪分类混淆矩阵Fig.4 Emotion classification confusion matrix
    表 1 本文提取的特征Table 1 Features extracted in this research
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张进,许子明,周月莹,王澎湃,张道强.基于脑电的虚拟现实诱发下情绪状态分类[J].数据采集与处理,2021,36(6):1226-1236

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  • 收稿日期:2021-04-20
  • 最后修改日期:2021-10-13
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  • 在线发布日期: 2021-12-14