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Hybrid Network Feature Extraction for Depression Assessment from Speech.

, , , , , , and . INTERSPEECH, page 4956-4960. ISCA, (2020)

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Exploring the interpretability in speech-based adolescent depression detection by SHAP., , , , and . ICCIP, page 562-567. ACM, (2023)AMINN: Attention-Based Multi-Information Neural Network for Emotion Recognition., , , , , and . ICCPR, page 56-62. ACM, (2020)Enhancing Modal Fusion by Alignment and Label Matching for Multimodal Emotion Recognition., , , , and . CoRR, (2024)Learning from Perturbations: Diverse and Informative Dialogue Generation with Inverse Adversarial Training., , and . ACL/IJCNLP (1), page 694-703. Association for Computational Linguistics, (2021)Learning to Predict Persona Information for Dialogue Personalization without Explicit Persona Description., , and . ACL (Findings), page 2979-2991. Association for Computational Linguistics, (2023)FTA-net: A Frequency and Time Attention Network for Speech Depression Detection., , , , and . INTERSPEECH, page 1723-1727. ISCA, (2023)Concss: Contrastive-based Context Comprehension for Dialogue-Appropriate Prosody in Conversational Speech Synthesis., , , , , , , , and . ICASSP, page 10706-10710. IEEE, (2024)Frame-Level Emotional State Alignment Method for Speech Emotion Recognition., , , , , , and . ICASSP, page 11486-11490. IEEE, (2024)Mining High-quality Samples from Raw Data and Majority Voting Method for Multimodal Emotion Recognition., , and . ACM Multimedia, page 9546-9550. ACM, (2023)Connecting the Dots Between Fact Verification and Fake News Detection., and . COLING, page 1820-1825. International Committee on Computational Linguistics, (2020)