基于可视化技术的智能交互式音乐信息研究

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ningjie Liao
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引用次数: 2

摘要

将图像与音乐相结合是一种加深对音乐信息的认识和理解的音乐可视化。本研究简要介绍了音乐可视化的概念,利用卷积神经网络和长短期记忆对音乐和图像进行配对,实现音乐可视化。然后,在损失函数中加入情感分类损失函数,充分利用音乐和图像中的情感信息。最后进行了仿真实验。结果表明:当情感分类损失函数的权重为0.2时,改进的基于深度学习的音乐可视化算法匹配准确率最高;与传统的关键词匹配方法和未改进的深度学习音乐可视化算法相比,改进的算法匹配出更合适的图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on intelligent interactive music information based on visualization technology
Abstract Combining images with music is a music visualization to deepen the knowledge and understanding of music information. This study briefly introduced the concept of music visualization and used a convolutional neural network and long short-term memory to pair music and images for music visualization. Then, an emotion classification loss function was added to the loss function to make full use of the emotional information in music and images. Finally, simulation experiments were performed. The results showed that the improved deep learning-based music visualization algorithm had the highest matching accuracy when the weight of the emotion classification loss function was 0.2; compared with the traditional keyword matching method and the nonimproved deep learning music visualization algorithm, the improved algorithm matched more suitable images.
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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