Titlebook: HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments; 24th International C Masaaki Kurosu,Saka

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Applying Generative Adversarial Networks and?Vision Transformers in?Speech Emotion Recognitionhe Vision Transformer (ViT) is being used. ViT has originally been applied for image classification, but in the current study is being adopted for emotion recognition. The proposed methods have been evaluated using the English IEMOCAP and the Japanese JTES speech corpora and showed significant improvements when data augmentation has been applied.

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annexation

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https://doi.org/10.1007/978-1-349-08415-9ations in the entire range in front of a display. In this method, we use a technique of FOV division, which transforms an input omnidirectional camera image into multiple perspective projection images with virtually rotating the camera, in order to avoid distortion in the peripheral area of a perspe

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The Politics of Divergent Policy,ficant contribution. Surprisingly, the field of emotion recognition is dominated by static machine learning approaches that do not account for the dynamics present in emotional processes. To overcome this limitation, we applied nonlinear autoregressive (NARX) models to predict emotion intensity from

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