NDLI: Exploiting turn-taking temporal evolution for personality trait perception in dyadic conversations

Content Provider	ACM Digital Library
Author	Su, Ming-Hsiang Wu, Chung-Hsien Zheng, Yu-Ting
Copyright Year	2016
Abstract	In dyadic conversations, turn-taking is a dynamically evolving behavior strongly linked to paralinguistic communication. Turn-taking temporal evolution in a dyadic conversation is inevitable and can be incorporated into a modeling framework for characterizing and recognizing the personality traits (PTs) of two speakers. This study presents an approach to automatically predicting PTs in a dyadic conversation. First, a recurrent neural network (RNN) was used to model the relationship between Big Five Inventory 10 (BFI-10) items and linguistic features of spoken text in each turn of a speaker (speaker turn) to output a BFI-10 profile. The RNN applies a recurrent property to characterize the short-term temporal evolution of a dialog. Second, the coupled hidden Markov model (C-HMM) was employed to model the long-term turn-taking temporal evolution and cross-speaker contextual information for detecting the PTs of two individuals for the entire dialog represented by the BFI-10 profile sequence. The Mandarin Conversational Dialogue Corpus was used for evaluation. The evaluation result shows that an average perception accuracy of 79.66% for the big five traits was achieved using five-fold cross validation. Compared with conventional HMM and support vector machine-based methods, the proposed approach achieved a more favorable performance according to a statistical significance test. The encouraging results confirm the usability of this system for future applications.
Starting Page	733
Ending Page	744
Page Count	12
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	4
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-04-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Big-five personality trait Coupled hidden markov model Dyadic conversation Personality trait perception
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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