Pregled bibliografske jedinice broj: 711607
How Do you Like Your Virtual Agent?: Human-agent Interaction Experience through Nonverbal Features and Personality Traits
How Do you Like Your Virtual Agent?: Human-agent Interaction Experience through Nonverbal Features and Personality Traits // Lecture notes in computer science, 8749 (2014), 1-15 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 711607 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
How Do you Like Your Virtual Agent?: Human-agent Interaction Experience through Nonverbal Features and Personality Traits
Autori
Čereković, Aleksandra ; Aran, Oya ; Gatica- Perez, Daniel
Izvornik
Lecture notes in computer science (0302-9743) 8749
(2014);
1-15
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
human-agent interaction ; quality of interaction ; nonverbal behavior ; Big 5 personality traits
Sažetak
Recent studies suggest that human interaction experience with virtual agents can be, to a very large degree, described by people’s personality traits. Moreover, the nonverbal behavior of a person has been known to indicate several social constructs in different settings. In this study, we analyze human-agent interaction from the perspective of the personality of the human and the nonverbal behaviors he/she displays during the interaction. Based on existing work in psychology, we designed and recorded an experiment on human-agent interactions, in which a human communicates with two different virtual agents. Human-agent interactions are described with three self-reported measures: quality, rapport and likeness of the agent. We investigate the use of self-reported personality traits and extracted audio-visual nonverbal features as descriptors of these measures. Our results on a correlation analysis show significant correlations between the interaction measures and several of the personality traits and nonverbal features, which are supported by both psychology and human-agent interaction literature. We further use traits and nonverbal cues as features to build regression models for predicting measures of interaction experience. The best results are obtained when nonverbal cues and personality traits are used together
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
HRZZ-PD-02.03/169 - Sustav Kinect kao alat za obradu društvenih signala
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Aleksandra Čereković
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus