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Research on Intelligent Recognition and Classification Algorithm of Music Emotion in Complex System of Music Performance

机译:复杂音乐性能系统音乐情感智能识别与分类算法研究

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In the complex system of music performance, there are differences in the expression of music emotions by listeners, so it is of great significance to study the classification of different emotions under different audio signals. In this paper, the research of human emotional intelligence recognition and classification algorithm in the complex system of music performance is proposed. Through the recognition of SVM, KNN, ANN, and ID3 classifiers, the accuracy of a single classifier is compared, and then the four classifiers are combined to compare the classification accuracy of audio signals before and after preprocessing. The results show that the accuracy of SVM and ANN fusion is the highest. Finally, recall and F 1 are comprehensively compared in the fusion algorithm, and the fusion classification effect of SVM and ANN is better than that of the algorithm model.
机译:在复杂的音乐表现系统中,听众表达音乐情绪的表达差异,因此研究不同音频信号下不同情绪的分类是具有重要意义。 本文提出了一种研究音乐性能复杂系统中的人类情报识别与分类算法的研究。 通过识别SVM,KNN,ANN和ID3分类器,比较了单个分类器的精度,然后组合四分类器以比较预处理前后音频信号的分类精度。 结果表明,SVM和ANN融合的准确性最高。 最后,在融合算法中综合比较了召回和F 1,SVM和ANN的融合分类效果优于算法模型。

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