On the MC-EIU dataset, semi-supervised training with HuBERT and RoBERTa plus late fusion raises joint emotion and intent recognition scores above unimodal baselines.
Fast yet effective speech emotion recognition with self-distillation,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.SD 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
End-to-end Acoustic-linguistic Emotion and Intent Recognition Enhanced by Semi-supervised Learning
On the MC-EIU dataset, semi-supervised training with HuBERT and RoBERTa plus late fusion raises joint emotion and intent recognition scores above unimodal baselines.