Interlocutor personality perception based on BFI profiles and coupled HMMs in a dyadic conversation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Previous studies have found systematic associations between personality and individual differences in interpersonal communication. Recently, researchers used various features to analyze individual personality traits in speech, social media content and essays. While few studies focused on detecting the personality interaction between two interlocutors, this paper presents a new approach to automatically and simultaneously predict the personalities of two interlocutors in a dyadic conversation. First, the recurrent neural networks (RNNs) are adopted to project the linguistic features of the transcribed spoken text of the input speech to the Big Five Inventory (BFI) space. The Coupled hidden Markov models (coupled HMMs) are then used to predict the interlocutor personality from the transcribed text of the two speakers considering the conversational interaction in their dialogue turns. The Mandarin Conversational Dialogue Corpus (MCDC) was adopted to evaluate the performance on interlocutor personality perception. Experimental results show that the proposed approach achieved satisfactory results in predicting personalities of two interlocutors at the same time.

Original languageEnglish
Title of host publicationProceedings of the 9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014
EditorsThomas Fang Zheng, Haizhou Li, Minghui Dong, Jianhua Tao, Yanfeng Lu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages178-182
Number of pages5
ISBN (Electronic)9781479942206
DOIs
Publication statusPublished - 2014 Oct 24
Event9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014 - Singapore, Singapore
Duration: 2014 Sep 122014 Sep 14

Publication series

NameProceedings of the 9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014

Other

Other9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014
CountrySingapore
CitySingapore
Period14-09-1214-09-14

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Software

Fingerprint Dive into the research topics of 'Interlocutor personality perception based on BFI profiles and coupled HMMs in a dyadic conversation'. Together they form a unique fingerprint.

  • Cite this

    Su, M. H., Zheng, Y. T., & Wu, C. H. (2014). Interlocutor personality perception based on BFI profiles and coupled HMMs in a dyadic conversation. In T. F. Zheng, H. Li, M. Dong, J. Tao, & Y. Lu (Eds.), Proceedings of the 9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014 (pp. 178-182). [6936634] (Proceedings of the 9th International Symposium on Chinese Spoken Language Processing, ISCSLP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCSLP.2014.6936634