Speech-Based Emotion Recognition with Self-Supervised Models Using Attentive Channel-Wise Correlations and Label Smoothing

Author:

Kakouros Sofoklis1,Stafylakis Themos2,Mošner Ladislav3,Burget Lukáš3

Affiliation:

1. University of Helsinki,Finland

2. Omilia - Conversational Intelligence,Athens,Greece

3. Faculty of Information Technology, Speech@FIT,Brno University of Technology,Czechia

Funder

Academy of Finland

National Science Foundation

Publisher

IEEE

Cited by 7 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. Cochceps-Augment: A Novel Self-Supervised Contrastive Learning Using Cochlear Cepstrum-Based Masking for Speech Emotion Recognition;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

2. Emotion Neural Transducer for Fine-Grained Speech Emotion Recognition;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Frame-Level Emotional State Alignment Method for Speech Emotion Recognition;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. Enhanced deadbeat predictive current control with novel generalized space vector modulation for five‐level inverter fed permanent magnet synchronous motor drive with reduced torque ripples and less computational burden;International Journal of Circuit Theory and Applications;2024-01-25

5. Stream-based Active Learning for Speech Emotion Recognition via Hybrid Data Selection and Continuous Learning;Lecture Notes in Computer Science;2024

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