  Research on human spoken language has shown that speech plays an important
role in identifying speaker personality traits. In this work, we propose an
approach for identifying speaker personality traits using overlap dynamics in
multiparty spoken dialogues. We first define a set of novel features
representing the overlap dynamics of each speaker. We then investigate the
impact of speaker personality traits on these features using ANOVA tests. We
find that features of overlap dynamics significantly vary for speakers with
different levels of both Extraversion and Conscientiousness. Finally, we find
that classifiers using only overlap dynamics features outperform random
guessing in identifying Extraversion and Agreeableness, and that the
improvements are statistically significant.
