Semantic Characteristics of Schizophrenic Speech

Kfir Bar, Vered Zilberstein, Ido Ziv, Heli Baram, Nachum Dershowitz, Samuel Itzikowitz, Eiran Vadim Harel


Abstract
Natural language processing tools are used to automatically detect disturbances in transcribed speech of schizophrenia inpatients who speak Hebrew. We measure topic mutation over time and show that controls maintain more cohesive speech than inpatients. We also examine differences in how inpatients and controls use adjectives and adverbs to describe content words and show that the ones used by controls are more common than the those of inpatients. We provide experimental results and show their potential for automatically detecting schizophrenia in patients by means only of their speech patterns.
Anthology ID:
W19-3010
Volume:
Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Kate Niederhoffer, Kristy Hollingshead, Philip Resnik, Rebecca Resnik, Kate Loveys
Venue:
CLPsych
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
84–93
Language:
URL:
https://aclanthology.org/W19-3010
DOI:
10.18653/v1/W19-3010
Bibkey:
Cite (ACL):
Kfir Bar, Vered Zilberstein, Ido Ziv, Heli Baram, Nachum Dershowitz, Samuel Itzikowitz, and Eiran Vadim Harel. 2019. Semantic Characteristics of Schizophrenic Speech. In Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, pages 84–93, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Semantic Characteristics of Schizophrenic Speech (Bar et al., CLPsych 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-3010.pdf