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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 BUT-FIT at SemEval-2020 Task 4: Multilingual commonsense ... Jon, Josef; Fajčík, Martin; Dočekal, Martin. - : arXiv, 2020 BASE Show details 2 Multimodal emotion recognition for AVEC 2016 challenge Hradis, Michal; Smrz, Pavel; Wood, Ian; Robin, Cécile; Matejka, Pavel; Otrusina, Lubomir; Popkova, Anna; Lamel, Lori; Povolny, Filip. - : ACM, 2017 Abstract: This paper describes a systems for emotion recognition and its application on the dataset from the AV+EC 2016 Emotion Recognition Challenge. The realized system was produced and submitted to the AV+EC 2016 evaluation, making use of all three modalities (audio, video, and physiological data). Our work primarily focused on features derived from audio. The original audio features were complement with bottleneck features and also text-based emotion recognition which is based on transcribing audio by an automatic speech recognition system and applying resources such as word embedding models and sentiment lexicons. Our multimodal fusion reached CCC=0.855 on dev set for arousal and 0.713 for valence. CCC on test set is 0.719 and 0.596 for arousal and valence respectively. ; 5. ACKNOWLEDGMENTS This work has been funded by the European Union’s Horizon 2020 programme under grant agreement No. 644632 MixedEmotions and No. 645523 BISON, and by Technology Agency of the Czech Republic project No. TA04011311 “MINT”. It was also supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Defense US Army Research Laboratory contract number W911NF- 12-C-0013. ; peer-reviewed Keyword: Arousal; Bottleneck features; Emotion recognition; Neural networks; Regression; Speech transcription; Valence; Word embedding URL: https://doi.org/10.1145/2988257.2988268 http://hdl.handle.net/10379/7036 BASE Hide details 3 Multimodal Emotion Recognition for AVEC 2016 Challenge Povolny, Filip; Matejka, Pavel; Hradis, Michal... In: Audio/Visual Emotion Challenge ; https://hal.archives-ouvertes.fr/hal-01837203 ; Audio/Visual Emotion Challenge, ACM, Oct 2016, Amsterdam, Netherlands (2016) BASE Show details 4 The sketch engine Kilgarriff, Adam; Rychly, Pavel; Smrž, Pavel... In: Practical lexicography (Oxford, 2008), p. 297-306 MPI für Psycholinguistik Show details 5 A parallel metagrammar for closely related languages - a case study for Czech and Russian Smrž, Pavel In: Research on language and computation. - London : King's College 3 (2005) 2-3, 165-189 BLLDB Show details

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