Introduces the eJSL Dialog dataset (1,920 videos in 480 dialogues from STUDIES corpus) for conversational sign language emotion recognition and benchmarks models revealing a domain gap with generic multimodal approaches.
A comprehensive review of multimodal emotion recognition: Techniques, challenges, and future directions,
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HQTN-SER combines a low-parameter quantum tensor network module with classical latent embeddings to reach 73-80% accuracy on three speech emotion datasets while using few qubits and showing stable training.
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HQTN-SER: Speech Emotion Recognition with Hybrid Quantum Tensor Networks
HQTN-SER combines a low-parameter quantum tensor network module with classical latent embeddings to reach 73-80% accuracy on three speech emotion datasets while using few qubits and showing stable training.