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Emotion Unfolding and Affective Scenes: A Case Study in Spoken Conversations.

, , and . ERM4CT@ICMI, page 5-11. ACM, (2015)

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Spoken language understanding with kernels for syntactic/semantic structures., , and . ASRU, page 183-188. IEEE, (2007)Active learning for automatic speech recognition., , and . ICASSP, page 3904-3907. IEEE, (2002)Fusion of acoustic, linguistic and psycholinguistic features for Speaker Personality Traits recognition., and . ICASSP, page 955-959. IEEE, (2014)Error Prediction in Spoken Dialog: From Signal-to-Noise Ratio to Semantic Confidence Scores., , , and . ICASSP (1), page 1041-1044. IEEE, (2005)Predicting Student Progress from Peer-Assessment Data., , and . EDM, page 270-275. International Educational Data Mining Society (IEDMS), (2016)Annotation and prediction of stress and workload from physiological and inertial signals., , and . EMBC, page 1621-1624. IEEE, (2015)Adaptive categorical understanding for spoken dialogue systems., , and . IEEE Trans. Speech Audio Process., 13 (3): 321-329 (2005)Evaluation of interpretability for deep learning algorithms in EEG emotion recognition: A case study in autism., , , , and . Artif. Intell. Medicine, (September 2023)Response Generation in Longitudinal Dialogues: Which Knowledge Representation Helps?, , and . CoRR, (2023)POMDP concept policies and task structures for hybrid dialog management., , , and . ICASSP, page 5592-5595. IEEE, (2011)