In recent years,convolutional neural networks(CNNs)become popular approaches used in music information retrieval(MIR)tasks,such as mood recognition,music auto-tagging and so on.Since CNNs are able to extract the local...In recent years,convolutional neural networks(CNNs)become popular approaches used in music information retrieval(MIR)tasks,such as mood recognition,music auto-tagging and so on.Since CNNs are able to extract the local features effectively,previous attempts show great performance on music auto-tagging.However,CNNs is not able to capture the spatial features and the relationship between low-level features are neglected.Motivated by this problem,a hybrid architecture is proposed based on Capsule Network,which is capable to extract spatial features with the routing-by-agreement mechanism.The proposed model was applied in music auto-tagging.The results show that it achieves promising results of the ROC-AUC score of 90.67%.展开更多
基金Research Fund for Sichuan Science and Technology Program(GrantNo.2019YFG0190)Research on Sino-Tibetan multisource information acquisition,fusion,data mining and its application(Grant No.H04W170186).
文摘In recent years,convolutional neural networks(CNNs)become popular approaches used in music information retrieval(MIR)tasks,such as mood recognition,music auto-tagging and so on.Since CNNs are able to extract the local features effectively,previous attempts show great performance on music auto-tagging.However,CNNs is not able to capture the spatial features and the relationship between low-level features are neglected.Motivated by this problem,a hybrid architecture is proposed based on Capsule Network,which is capable to extract spatial features with the routing-by-agreement mechanism.The proposed model was applied in music auto-tagging.The results show that it achieves promising results of the ROC-AUC score of 90.67%.
