Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition
Author:
Affiliation:
1. Southeast University,Key Laboratory of Child Development and Learning Science of Ministry of Education,Nanjing,China
2. Imperial College,GLAM - the Group on Language, Audio, & Music,London,UK
Funder
China Postdoctoral Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447726.pdf?arnumber=10447726
Reference23 articles.
1. Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models
2. Domain Invariant Feature Learning for Speaker-Independent Speech Emotion Recognition
3. A Comprehensive Review of Speech Emotion Recognition Systems
4. Databases, features and classifiers for speech emotion recognition: a review
5. A systematic literature review of speech emotion recognition approaches
Cited by 2 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. Discriminative feature learning based on multi-view attention network with diffusion joint loss for speech emotion recognition;Engineering Applications of Artificial Intelligence;2024-11
2. Speech emotion recognition using the novel SwinEmoNet (Shifted Window Transformer Emotion Network);International Journal of Speech Technology;2024-07-10
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