Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue

Mingzhi Yu, Emer Gilmartin, Diane Litman


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.


 DOI: 10.21437/Interspeech.2019-1886

Cite as: Yu, M., Gilmartin, E., Litman, D. (2019) Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue. Proc. Interspeech 2019, 1921-1925, DOI: 10.21437/Interspeech.2019-1886.


@inproceedings{Yu2019,
  author={Mingzhi Yu and Emer Gilmartin and Diane Litman},
  title={{Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={1921--1925},
  doi={10.21437/Interspeech.2019-1886},
  url={http://dx.doi.org/10.21437/Interspeech.2019-1886}
}