Speech Emotion Recognition Using Semi-Supervised Learning with Efficient Labeling Strategies
Author:
Affiliation:
1. Fairy Devices Inc.,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9687821/9687855/09687938.pdf?arnumber=9687938
Reference29 articles.
1. Semi-supervised Ladder Networks for Speech Emotion Recognition
2. Semi-supervised speech emotion recognition with ladder networks;parth;IEEE/ACM Transactions on Acousics Speech and Sig-nal Processing,2020
3. Multi-Task Semi-Supervised Adversarial Autoencoding for Speech Emotion Recognition
4. Self-Training With Noisy Student Improves ImageNet Classification
5. Leveraging Unlabeled Data for Emotion Recognition With Enhanced Collaborative Semi-Supervised Learning
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4. Semi-Supervised Multimodal Emotion Recognition with Class-Balanced Pseudo-labeling;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26
5. Domain Adaptation without Catastrophic Forgetting on a Small-Scale Partially-Labeled Corpus for Speech Emotion Recognition;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04
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