University of Hertfordshire

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Original languageEnglish
Article number2930695
JournalIEEE Transactions on Affective Computing
Early online date23 Jul 2019
Publication statusE-pub ahead of print - 23 Jul 2019


This work shows that fillers - short utterances like "ehm" and "uhm" - allow one to predict whether someone is above median along the Big-Five personality traits. The experiments have been performed over a corpus of 2,988 fillers uttered by 120 different speakers in spontaneous conversations. The results show that the prediction accuracies range between 74% and 82% depending on the particular trait. The proposed approach includes a feature selection step - based on Quantum Evolutionary Algorithms - that has been used to detect the personality markers, i.e., the subset of the features that better account for the prediction outcomes and, indirectly, for the personality of the speakers. The results show that only a relatively few features tend to be consistently selected, thus acting as reliable personality markers.

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