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    Wyświetlanie 1-5 z 5
    Tytuł:
    From words to emoticons : deep emotion recognition in text and its wider implications
    Autorzy:
    Ptaszynski, Michal
    Takizawa, Mitsuru
    Rzepka, Rafal
    Araki, Kenji
    Vallverdú, Jordi
    Dybała, Paweł
    Opis:
    This paper summarizes several lexical methods for more comprehensive affect recognition in text usingan example of typed utterances. We introduce a set of algorithms that are capable of recognizing emotions of user’sstatements in order to achieve more effective and smoother human-machine conversation. Aspects often neglectedby existing systems working with Japanese language, e.g. compound sentences, double negation sentences, modifiersas adverbs and emoticons were combined and their higher effectiveness in recognizing affect in more complicatedsentences was confirmed through evaluation experiments. The results are introduced together with separate analysisof emoticons’ influence on emotional load. We also discuss importance of predicting human emotions not only in thefield of human-computer interaction but also its meaning for developing ethical chatbo.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    Personality-based affective adaptation methods for intelligent systems
    Autorzy:
    Kutt, Krzysztof
    Nalepa, Grzegorz
    Bobek, Szymon
    Drążyk, Dominika
    Opis:
    In this article, we propose using personality assessment as a way to adapt affective intelligent systems. This psychologically-grounded mechanism will divide users into groups that differ in their reactions to affective stimuli for which the behaviour of the system can be adjusted. In order to verify the hypotheses, we conducted an experiment on 206 people, which consisted of two proof-of-concept demonstrations: a “classical” stimuli presentation part, and affective games that provide a rich and controllable environment for complex emotional stimuli. Several significant links between personality traits and the psychophysiological signals (electrocardiogram (ECG), galvanic skin response (GSR)), which were gathered while using the BITalino (r)evolution kit platform, as well as between personality traits and reactions to complex stimulus environment, are promising results that indicate the potential of the proposed adaptation mechanism.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    A study on the role of affective feedback in robot-assisted learning
    Autorzy:
    Indurkhya, Bipin
    Gunia, Artur
    Gruba, Łukasz
    Błażejowska, Gabriela
    Opis:
    In recent years, there have been many approaches to using robots to teach computer programming. In intelligent tutoring systems and computer-aided learning, there is also some research to show that affective feedback to the student increases learning efficiency. However, a few studies on the role of incorporating an emotional personality in the robot in robot-assisted learning have found different results. To explore this issue further, we conducted a pilot study to investigate the effect of positive verbal encouragement and non-verbal emotive behaviour of the Miro-E robot during a robot-assisted programming session. The participants were tasked to program the robot’s behaviour. In the experimental group, the robot monitored the participants’ emotional state via their facial expressions, and provided affective feedback to the participants after completing each task. In the control group, the robot responded in a neutral way. The participants filled out a questionnaire before and after the programming session. The results show a positive reaction of the participants to the robot and the exercise. Though the number of participants was small, as the experiment was conducted during the pandemic, a qualitative analysis of the data was carried out. We found that the greatest affective outcome of the session was for students who had little experience or interest in programming before. We also found that the affective expressions of the robot had a negative impact on its likeability, revealing vestiges of the uncanny valley effect.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
    Tytuł:
    Datasets for automated affect and emotion recognition from cardiovascular signals using artificial intelligence- a systematic review
    Autorzy:
    Żabicka, Wioletta
    Ligęza, Antoni
    Szymkowski, Mateusz
    Storman, Dawid
    Mamica, Maria
    Wojtaszek-Główka, Magdalena
    Jemioło, Paweł
    Opis:
    Our review aimed to assess the current state and quality of publicly available datasets used for automated affect and emotion recognition (AAER) with artificial intelligence (AI), and emphasising cardiovascular (CV) signals. The quality of such datasets is essential to create replicable systems for future work to grow. We investigated nine sources up to 31 August 2020, using a developed search strategy, including studies considering the use of AI in AAER based on CV signals. Two independent reviewers performed the screening of identified records, full-text assessment, data extraction, and credibility. All discrepancies were resolved by discussion. We descriptively synthesised the results and assessed their credibility. The protocol was registered on the Open Science Framework (OSF) platform. Eighteen records out of 195 were selected from 4649 records, focusing on datasets containing CV signals for AAER. Included papers analysed and shared data of 812 participants aged 17 to 47. Electrocardiography was the most explored signal (83.33% of datasets). Authors utilised video stimulation most frequently (52.38% of experiments). Despite these results, much information was not reported by researchers. The quality of the analysed papers was mainly low. Researchers in the field should concentrate more on methodology.
    Dostawca treści:
    Repozytorium Uniwersytetu Jagiellońskiego
    Artykuł
      Wyświetlanie 1-5 z 5

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