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IEMOCAP: interactive emotional dyadic motion capture database.

, , , , , , , , and . Language Resources and Evaluation, 42 (4): 335-359 (2008)

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Shape-based modeling of the fundamental frequency contour for emotion detection in speech., , and . Computer Speech & Language, 28 (1): 278-294 (2014)Modeling mutual influence of interlocutor emotion states in dyadic spoken interactions., , , and . INTERSPEECH, page 1983-1986. ISCA, (2009)Analysis and Compensation of the Reaction Lag of Evaluators in Continuous Emotional Annotations., and . ACII, page 85-90. IEEE Computer Society, (2013)Detecting Sleepiness by Fusing Classifiers Trained with Novel Acoustic Features., , , , , and . INTERSPEECH, page 3285-3288. ISCA, (2011)Evaluation of syllable rate estimation in expressive speech and its contribution to emotion recognition., and . SLT, page 472-477. IEEE, (2014)A personalized emotion recognition system using an unsupervised feature adaptation scheme., and . ICASSP, page 5117-5120. IEEE, (2012)A real-time protocol for the Internet based on the least mean square algorithm., , and . IEEE Trans. Multimedia, 6 (1): 174-184 (2004)Building a naturalistic emotional speech corpus by retrieving expressive behaviors from existing speech corpora., , and . INTERSPEECH, page 238-242. ISCA, (2014)Predicting Categorical Emotions by Jointly Learning Primary and Secondary Emotions through Multitask Learning., and . INTERSPEECH, page 951-955. ISCA, (2018)Defining Emotionally Salient Regions Using Qualitative Agreement Method., and . INTERSPEECH, page 3598-3602. ISCA, (2016)