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| pub:research [2021/02/02 18:50] – ICAISC2020 added kkutt | pub:research [2022/04/29 12:41] – kkutt | ||
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| ===== Papers ===== | ===== Papers ===== | ||
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| + | === MRC2021b === | ||
| + | * L. Żuchowska, K. Kutt, and G. J. Nalepa, " | ||
| + | * {{http:// | ||
| + | * ++Abstract | The paper presents the design of a game that will serve as a research environment in the BIRAFFE series experiment planned for autumn 2021, which uses affective and personality computing methods to develop methods for interacting with intelligent assistants. A key aspect is grounding the game design on the taxonomy of player types designed by Bartle. This will allow for an investigation of hypotheses concerning the characteristics of particular types of players or their stability in response to emotionally-charged stimuli occurring during the game.++ | ||
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| + | === MRC2021a === | ||
| + | * K. Kutt, L. Żuchowska, S. Bobek, and G. J. Nalepa, " | ||
| + | * {{http:// | ||
| + | * ++Abstract | The paper provides insights into two main threads of analysis of the BIRAFFE2 dataset concerning the associations between personality and physiological signals and concerning the game logs' generation and processing. Alongside the presentation of results, we propose the generation of event-marked maps as an important step in the exploratory analysis of game data. The paper concludes with a set of guidelines for using games as a context-rich experimental environment.++ | ||
| === Sensors2021 === | === Sensors2021 === | ||
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| * ++Abstract | We are aiming at developing a technology to detect, identify and interpret human emotional states. We believe, that it can be provided based on the integration of context-aware systems and affective computing paradigms. We are planning to identify and characterize affective context data, and provide knowledge-based models to identify and interpret affects based on this data. A working name for this technology is simply AfCAI: Affective Computing with Context Awareness for Ambient Intelligence.++ | * ++Abstract | We are aiming at developing a technology to detect, identify and interpret human emotional states. We believe, that it can be provided based on the integration of context-aware systems and affective computing paradigms. We are planning to identify and characterize affective context data, and provide knowledge-based models to identify and interpret affects based on this data. A working name for this technology is simply AfCAI: Affective Computing with Context Awareness for Ambient Intelligence.++ | ||
| + | ===== Projects ===== | ||
| + | |||
| + | * **Personality, | ||
| ===== Tools and Datasets ===== | ===== Tools and Datasets ===== | ||
kkutt