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Emotion Recognition of Violin Music based on Strings Music Theory for Mascot Robot System

机译:基于琴弦音乐理论对吉祥物机器人系统的情感认识

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Emotion recognition of violin music is proposed based on strings music theory, where the emotional state of violin music is expressed by Affinity-Pleasure-Arousal emotion space. Besides the music features from audio processing, three features (i.e., left-hand feature, right-hand feature, and dynamics) with regard to both composition and performance of violin music, are extracted to improve the emotion recognition of violin music. To demonstrate the validity of this proposal, a dataset composing of 120 pieces of author-performed violin music with six primary emotion categories is established, by which the experimental results of emotion recognition using Support Vector Regression report overall recognition accuracy of 86.67%. The proposal could be an integral part for analyzing the communication atmosphere with background music, or be used by a music recommendation system for various occasions.
机译:基于琴弦音乐理论提出了小提琴音乐的情感认可,其中小提琴音乐的情感状态是由亲和力的令人兴奋的情感空间表示的。除了来自音频处理的音乐功能,提取了关于小提琴音乐的组成和性能的三个特征(即左手特征,右手特征和动态),以改善小提琴音乐的情感识别。为了证明这一提案的有效性,建立了120件作家执行的小提琴音乐的数据集组成,其中具有六个主要情感类别的六个主要情绪类别,通过支持向量回归报告总识别准确性为86.67%的情况。该提议可以是用于分析与背景音乐的通信气氛的组成部分,或者由音乐推荐系统用于各种场合。

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