Application of Ethnic Music Retrieval System Integrating Multimodal Attention Mechanism in Humanoid Robot Education Interaction

With the rapid development of Internet technology and multimedia applications, and the continuous expansion of interactive scenes of humanoid robot education, the number of digital resources of ethnic music has reached an unprecedented scale and continues to grow. This study mainly focuses on the construction of a national music retrieval system that integrates multimodal attention mechanisms and its application implementation in humanoid robot education interaction. Firstly, a method for automatic annotation of ethnic music adapted to multimodal data was studied to meet the human-computer interaction needs of robot education interaction. Secondly, a label conditional random field music automatic annotation method is proposed, and a multi-modal attention mechanism deep neural network model for ethnic music annotation is constructed to enhance the accurate matching of music features and retrieval requirements in human-computer interaction. Finally, integrate the constructed ethnic music retrieval system into the humanoid robot education interactive platform, conduct application analysis based on actual educational interactive scenarios, verify the effectiveness of the system in the human-computer interaction process, and complete performance evaluation. The results indicate that in the Glu module, Glu blocks perform better in ethnic music annotation tasks. The annotation results of various indicators in music hierarchy sequence modeling are superior to traditional models, ensuring the accuracy of ethnic music annotation in human-computer interaction scenarios. Compared with other algorithms, the AUC label score of this system is the highest, reaching 0.913. It can more efficiently model the mapping relationship between multimodal music features input during human-computer interaction and text retrieval requirements. It shows better performance in all evaluation indicators and can effectively support ethnic music retrieval services in humanoid robot education interaction, enhancing the immersion and fun of educational interaction.