Construction of multimodal music automatic annotation model based on neural network algorithm

Miao, Zhong; Cheng, Chaozhi

doi:10.1117/12.2689482

Cited by 2 publications

(1 citation statement)

References 9 publications

(7 reference statements)

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“…For example, in dealing with complex teaching scenarios, existing technologies often struggle to accurately align and recognize relevant information across different modalities, leading to a discrepancy in the interactive experience compared to the intuitive feeling in real teaching environments [18,19]. In addition, regarding the automatic annotation and understanding of image content, current methods cannot adequately recognize and express the teaching semantics implied in images, limiting the functionality of remote teaching platforms [20].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Remote Teaching Interaction Platforms Through Multimodal Image Recognition Technology

Fang,

Zhang

2024

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In the context of the digital era, remote teaching has become an integral part of the global education system. Effective remote teaching relies on the high interactivity of interaction platforms and the precise delivery of teaching content, with multimodal image recognition technology playing a key role. This technology enhances the intelligence level of remote teaching platforms by integrating visual and textual information, providing a richer and more intuitive interactive experience for teachers and students. However, existing multimodal image recognition technologies still face challenges in accuracy, real-time performance, and semantic understanding, especially in complex teaching scenarios where the understanding and feedback on teaching content are not accurate enough, limiting the effectiveness of remote teaching interaction platforms. Addressing these limitations, this paper proposes a multimodal image alignment method based on a self-attention mechanism that effectively integrates visual information into an encoder-decoder model to achieve high consistency between images and teaching content. Additionally, a novel multimodal image annotation and recognition algorithm is introduced, considering both semantic information and visual saliency to achieve higher recognition accuracy and practicality. Experimental validation shows significant improvements in the accuracy and real-time performance of multimodal image recognition, providing strong technical support for remote teaching interaction platforms, optimizing the allocation of teaching resources, and enhancing the quality and efficiency of education.

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Section: Introductionmentioning

confidence: 99%

Optimizing Remote Teaching Interaction Platforms Through Multimodal Image Recognition Technology

Fang,

Zhang

2024

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Construction and Implementation of Content-Based National Music Retrieval Model Under Deep Learning

Shi,

Liu

2024

International Journal of Information System Modeling and Design

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This research mainly studies the construction and implementation of the content-based folk music retrieval model. Firstly, it studies the music automatic annotation method based on deep learning, and then proposes the tag conditional random field music automatic annotation method, and then constructs the music annotation depth neural network model combining a variety of music representation and attention mechanism. Finally, it analyzes the proposed folk music retrieval model the effectiveness of the cable model is verified and its performance is evaluated. The results show that in Glu module, Glu blocks had better performance in music annotation, and the music annotation results of each index in music hierarchical sequence modeling are better, which ensures the effectiveness of music annotation. Compared with other algorithms, the AUC tag score of the proposed method is the highest, which is 0.913; it can better model the mapping relationship between the audio features of music input to the text tag and has higher scores on all evaluation indicators.

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Construction of multimodal music automatic annotation model based on neural network algorithm

Cited by 2 publications

References 9 publications

Optimizing Remote Teaching Interaction Platforms Through Multimodal Image Recognition Technology

Optimizing Remote Teaching Interaction Platforms Through Multimodal Image Recognition Technology

Construction and Implementation of Content-Based National Music Retrieval Model Under Deep Learning

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