A hybrid semi-supervised framework fusing Whisper embeddings with acoustic and prosodic features achieves 0.751 Macro-F1 for speaker confidence detection and outperforms baselines including WavLM, HuBERT, and Wav2Vec 2.0.
Evidence for a three-factor theory of emotions
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Speech from self-control tasks in remote learning shows perceptible emotional variations along valence, arousal, and dominance that can be automatically predicted.
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A Semi-Supervised Framework for Speech Confidence Detection using Whisper
A hybrid semi-supervised framework fusing Whisper embeddings with acoustic and prosodic features achieves 0.751 Macro-F1 for speaker confidence detection and outperforms baselines including WavLM, HuBERT, and Wav2Vec 2.0.
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Toward using Speech to Sense Student Emotion in Remote Learning Environments
Speech from self-control tasks in remote learning shows perceptible emotional variations along valence, arousal, and dominance that can be automatically predicted.