An Efficient Bi-modal Fusion Framework for Music Emotion Recognition

IF 9.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Affective Computing Pub Date : 2024-10-24 DOI:10.1109/taffc.2024.3486340
Yao Xiao, Haoxin Ruan, Xujian Zhao, Peiquan Jin, Li Tian, Zihan Wei, Xuebo Cai, Yixin Wang, Liang Liu
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音乐情感识别的高效双模态融合框架
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来源期刊
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
15.00
自引率
6.20%
发文量
174
期刊介绍: The IEEE Transactions on Affective Computing is an international and interdisciplinary journal. Its primary goal is to share research findings on the development of systems capable of recognizing, interpreting, and simulating human emotions and related affective phenomena. The journal publishes original research on the underlying principles and theories that explain how and why affective factors shape human-technology interactions. It also focuses on how techniques for sensing and simulating affect can enhance our understanding of human emotions and processes. Additionally, the journal explores the design, implementation, and evaluation of systems that prioritize the consideration of affect in their usability. We also welcome surveys of existing work that provide new perspectives on the historical and future directions of this field.
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