Wenhui Shi, Yi Zhai, Weirong Li, Chong Shen, Xiaoming Shi
[Difference on sleeping between school-days and weekends in elementary school children, data from 8 provinces in China]
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
present multimodal genre recognition framework considers modalities audio text image features extracted audio signals album cover images lyrics music tracks contrast pure learning features neural network done related work handcrafted features designed respective modality also integrated allowing higher interpretability created models theoretical analysis impact individual features genre prediction genre recognition performed binary classification music track respect genre based combinations elementary features feature combination twolevel technique used combines aggregation fixedlength feature vectors confidencebased fusion classification results extensive experiments conducted three classifier models nave bayes support vector machine random forest numerous feature combinations results presented visually data reduction improved perceptibility achieved multiobjective analysis restriction nondominated data feature classifierrelated hypotheses formulated based data statistical significance formally analyzed statistical analysis shows combination two modalities almost always leads significant increase performance combination three modalities several cases