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Discourse Particles and User Characteristics in Naturalistic Human-Computer Interaction.

, , , and . HCI (2), volume 8511 of Lecture Notes in Computer Science, page 492-501. Springer, (2014)

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Zanzibar OpenIVR: An Open-Source Framework for Development of Spoken Dialog Systems., , , and . TSD, volume 6836 of Lecture Notes in Computer Science, page 372-379. Springer, (2011)Investigating the Form-Function-Relation of the Discourse Particle "hm" in a Naturalistic Human-Computer Interaction., , , , and . WIRN, volume 26 of Smart Innovation, Systems and Technologies, page 387-394. Springer, (2013)Vowels formants analysis allows straightforward detection of high arousal emotions., , , , , and . ICME, page 1-6. IEEE Computer Society, (2011)Application of image processing methods to filled pauses detection from spontaneous speech., , , and . INTERSPEECH, page 1816-1820. ISCA, (2014)Analysis of significant dialog events in realistic human-computer interaction., , , , , , , and . J. Multimodal User Interfaces, 8 (1): 75-86 (2014)Fine-tuning HMMS for nonverbal vocalizations in spontaneous speech: A multicorpus perspective., , and . ICASSP, page 4625-4628. IEEE, (2012)Discourse Particles and User Characteristics in Naturalistic Human-Computer Interaction., , , and . HCI (2), volume 8511 of Lecture Notes in Computer Science, page 492-501. Springer, (2014)Vowels Formants Analysis Allows Straightforward Detection of High Arousal Acted and Spontaneous Emotions., , , and . INTERSPEECH, page 1577-1580. ISCA, (2011)Language Modeling of Nonverbal Vocalizations in Spontaneous Speech., , , and . TSD, volume 7499 of Lecture Notes in Computer Science, page 488-495. Springer, (2012)Modeling phonetic pattern variability in favor of the creation of robust emotion classifiers for real-life applications., , , and . Computer Speech & Language, 28 (2): 483-500 (2014)