Music Emotion Classification Method Based on Deep Learning and Explicit Sparse Attention Network

Author:

Jia Xiaoguang1ORCID

Affiliation:

1. School of Music, Baotou Teachers’ College, lnner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014030, China

Abstract

In order to improve the accuracy of music emotion recognition and classification, this study combines an explicit sparse attention network with deep learning and proposes an effective emotion recognition and classification method for complex music data sets. First, the method uses fine-grained segmentation and other methods to preprocess the sample data set, so as to provide a high-quality input data sample set for the classification model. The explicit sparse attention network is introduced into the deep learning network to reduce the influence of irrelevant information on the recognition results and improve the emotion classification and recognition ability of music sample data set. The simulation experiment is based on the actual data set of the network. The experimental results show that the recognition accuracy of the proposed method is 0.71 for happy emotions and 0.688 for sad emotions. It has a good ability of music emotion recognition and classification.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Verse1-Chorus-Verse2 Structure: A Stacked Ensemble Approach for Enhanced Music Emotion Recognition;Applied Sciences;2024-07-01

2. Enhancing Tone Recognition in Large-Scale Social Media Data with Deep Learning and Big Data Processing;2023 5th International Conference on Artificial Intelligence and Computer Applications (ICAICA);2023-11-28

3. Music Emotion Recognition using Convolutional Neural Networks for Regional Languages;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02

4. Retracted: Music Emotion Classification Method Based on Deep Learning and Explicit Sparse Attention Network;Computational Intelligence and Neuroscience;2023-08-02

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