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EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine

机译:音乐听觉中基于脑电图的情感识别:多类支持向量机方案的比较

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Currently, how to equip machines with the ability for properly recognizing users' felt-emotion during multimedia presentation is a growing issue. In this study we focused on the approach for recognizing music-induced emotional responses from brain activity. A comparative study was conducted to testify the feasibility of using hierarchical binary classifiers to improve the classification performance as compared with nonhierarchical schemes. According to our classification results, we not only found that using one-against-one scheme of hierarchical binary classifier results in an improvement to performance, but also established an alternative solution for emotion recognition by proposed model-based scheme depending on 2D emotion model.
机译:当前,如何使机器具备在多媒体演示过程中正确识别用户的感觉情绪的能力正在成为一个日益严重的问题。在这项研究中,我们专注于识别音乐诱发的大脑活动引起的情绪反应的方法。进行了一项比较研究,以证明与非分层方案相比,使用分层二进制分类器来提高分类性能的可行性。根据我们的分类结果,我们不仅发现使用一对一的分层二元分类器方案可以改善性能,而且通过基于二维情感模型的基于模型的方案为情感识别建立了一种替代解决方案。

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