Szczegóły publikacji
Opis bibliograficzny
Emotion elicitation with stimuli datasets in automatic affect recognition studies – umbrella review / Paweł JEMIOŁO, Dawid Storman, Barbara GIŻYCKA, Antoni LIGĘZA // W: Human-Computer Interaction - INTERACT 2021 : 18th IFIP TC 13 international conference : Bari, Italy, August 30–September 3, 2021 : proceedings, Pt. 3 / eds. Carmelo Ardiot, [et al.]. — Cham : Springer Nature Switzerland ; IFIP International Federation for Information Processing, cop. 2021. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12934. Information Systems and Applications, incl. Internet/Web, and HCI). — ISBN: 978-3-030-85612-0; e-ISBN: 978-3-030-85613-7. — S. 248–269. — Bibliogr., Abstr. — Publikacja dostępna online od: 2021-08-26
Autorzy (4)
- AGHJemioło Paweł
- Storman Dawid
- AGHGiżycka Barbara
- AGHLigęza Antoni
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 135645 |
|---|---|
| Data dodania do BaDAP | 2021-09-23 |
| DOI | 10.1007/978-3-030-85613-7_18 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | IFIP TC13 Conference on Human-Computer Interaction |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Affect Recognition has become a relevant research field in Artificial Intelligence development. Nevertheless, its progress is impeded by poor methodological conduct in psychology, computer science, and, consequently, affective computing. We address this issue by providing a rigorous overview of Emotion Elicitation utilising stimuli datasets in Affect Recognition studies. We identified relevant trials by exploring five electronic databases and other sources. Eligible studies were those reviews identified through the title, abstract and full text, which aimed to include subjects who underwent Emotion Elicitation in laboratory conditions with passive stimuli presentation for Automatic Affect Recognition. Two independent reviewers were involved in each step in the process of identification of eligible studies. The discussion resolved any discrepancies. 16 of 1308 references met the inclusion criteria. The 16 papers reviewed 271 primary studies, in which 3515 participants were examined. We found out that datasets containing video, music, and pictures stimuli are most widely explored, while researchers should focus more on these incorporating audio excerpts. Five of the most frequently analysed emotions are: sadness, anger, happiness, fear and joyfulness. The Elicitation Effectiveness and techniques towards emotion assessment, are not reported by the review authors. We also provide conclusions about the lack of studies concerning Deep Learning methods. All of the included studies were of Critically low quality. Much of the critical information is missing in the reviewed papers, and therefore a comprehensive view on this research area is disturbingly hard to claim.