Abstract
This paper describes several systems for emotion recognition developed for the AV+EC 2015 Emotion Recognition Challenge. A complete system, making use of all three modalities (audio, video, and physiological data), was submitted to the evaluation. The focus of our work was, however, on the so called Bottle-Neck features used to complement the audio features. For the recognition of arousal, we improved the results of the delivered audio features and combined them favorably with the Bottle-Neck features. For valence, the best results were obtained with video, but a two-output Bottle-Neck structure is not far behind, which is especially appealing for applications where only audio is available.
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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. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoD/ARL, or the U.S. Government. Thanks to Fabien Ringeval for scoring several other systems after the deadline of AVEC 2015 which allowed us to make proper analysis for this paper.
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Popková, A., Povolný, F., Matějka, P., Glembek, O., Grézl, F., Černocký, J.“. (2016). Investigation of Bottle-Neck Features for Emotion Recognition. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_49
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DOI: https://doi.org/10.1007/978-3-319-45510-5_49
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