Abstract: Trustworthiness recognition attracts the attention of the research community due to its main role in social communications. However, few datasets are available and there are still many dimensions of trust to investigate. This paper presents a study of an annotation tool for creating of a trustworthiness corpus. Specifically, we asked the participants to rate shortemotional videos extracted from RAVDESS at zero acquaintance and studied the relationship between their trustworthiness score and other characteristics of the subjects of each video. Eloquence (ρ = 0.41), kindness (ρ = 0.32), attractiveness (ρ = 0.34), and authenticity of emotion transmitted (ρ = 0.6) are shown to be important determinants of perceived trustworthiness. In addition, we have measured a strong association between some of the variables under study. For example, physical beauty and voice pleasantness obtain a ρ = 0.71, or eloquence and expressiveness (ρ = 0.65), which opens a future line of investigation to study how people understand attractiveness and eloquence from these perspectives. Finally, an attribute selection strategy identified that frequency and spectral-related attributes could be accurate aural indicators of perceived trustworthiness.
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