Music generation based on emotional EEG

Gang Luo, Hao Chen, Zhengxiu Li, M. Wang
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引用次数: 2

Abstract

Transforming electroencephalogram (EEG) into music has been playing an important role in social life. How to generate music that can express a certain emotion state is a challenge for most of the existing generative models in the studies. To address the problem, a music generation method based on emotional EEG is proposed in this paper. In this method, sequence to sequence long-short term memory is utilized to train the emotional music to obtain emotional music generators, and support vector machine is used to get emotional information. The features related to emotion are extracted to map into musical parameters and emotion music generator is used to generate the emotional EEG music. The experimental results show that the music generated by the proposed method achieves a high performance with respect to both emotion-expressing and musicality.
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基于情绪脑电图的音乐生成
将脑电图转化为音乐在社会生活中发挥着重要的作用。如何生成能够表达某种情感状态的音乐,是目前研究中大多数生成模型面临的挑战。针对这一问题,本文提出了一种基于情绪脑电图的音乐生成方法。该方法利用序列对序列的长短期记忆对情感音乐进行训练,获得情感音乐生成器,并利用支持向量机获得情感信息。提取与情感相关的特征映射为音乐参数,利用情感音乐发生器生成情感脑电图音乐。实验结果表明,该方法生成的音乐在情感表达和音乐性方面都取得了较好的效果。
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