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Combining frame and turn-level information for robust recognition of emotions within speech.

, , , and . Interspeech, page 2249--2252. (2007)

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Annotators' agreement and spontaneous emotion classification performance., and . INTERSPEECH, page 1546-1550. ISCA, (2015)Heading toward to the natural way of human-machine interaction: the nimitek project., and . ICME, page 950-953. IEEE, (2009)Implementing Gender-Dependent Vowel-Level Analysis for Boosting Speech-Based Depression Recognition., , , and . INTERSPEECH, page 3266-3270. ISCA, (2017)Enhancing Speech-Based Depression Detection Through Gender Dependent Vowel-Level Formant Features., , , and . AIME, volume 10259 of Lecture Notes in Computer Science, page 209-214. Springer, (2017)Appropriate emotional labelling of non-acted speech using basic emotions, geneva emotion wheel and self assessment manikins., , , , and . ICME, page 1-6. IEEE Computer Society, (2011)Parameter Optimization Issues for Cross-corpora Emotion Classification., , and . ACII, page 454-459. IEEE Computer Society, (2013)Cross-corpus acoustic emotion recognition: Variances and strategies (Extended abstract)., , , , , , and . ACII, page 470-476. IEEE Computer Society, (2015)Emotion recognition within spoken dialog systems.. Otto von Guericke University Magdeburg, (2011)Implementing Fusion Techniques for the Classification of Paralinguistic Information., , , and . INTERSPEECH, page 526-530. ISCA, (2018)Combining speech recognition and acoustic word emotion models for robust text-independent emotion recognition., , , , and . ICME, page 1333-1336. IEEE Computer Society, (2008)