EmotionBox: A music-element-driven emotional music generation system based on music psychology - Zheng, Kaitong; Meng, Ruijie; Zheng, Chengshi; Li, Xiaodong; Sang, Jinqiu; Cai, Juanjuan; Wang, Jie; Wang, Xiao (Frontiers in Psychology, 2022)
With the development of deep neural networks, automatic music composition has made great progress. Although emotional music can evoke listeners' different auditory perceptions, only few researches have focused on generating emotional music. This paper presents EmotionBox -an music-element-driven emotional music generator based on music psychology that is capable of composing music given a specific emotion, while this model does not require a music dataset labeled with emotions as previous methods. In this work, pitch histogram and note density are extracted as features that represent mode and tempo respectively to control music emotions. The specific emotions are mapped from these features through Russell's psychology model. The subjective listening tests show that the Emotionbox has a competitive performance on generating different emotional music and significantly better performance on generating music with low arousal emotions compared with the emotion-label-based method.