Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/105913
Title: | Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia | Authors: | Tahir, Yasir Yang, Zixu Chakraborty, Debsubhra Thalmann, Nadia Thalmann, Daniel Maniam, Yogeswary Tan, Bhing-Leet Dauwels, Justin Nur Amirah Abdul Rashid Lee, Jimmy Chee Keong |
Keywords: | Verbal Communication DRNTU::Science::Medicine Speech |
Issue Date: | 2019 | Source: | Tahir, Y., Yang, Z., Chakraborty, D., Thalmann, N., Thalmann, D., Maniam, Y., . . . Dauwels, J. (2019). Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia. PLOS ONE, 14(4), e0214314-. doi:10.1371/journal.pone.0214314 | Series/Report no.: | PLOS ONE | Abstract: | Negative symptoms in schizophrenia are associated with significant burden and possess little to no robust treatments in clinical practice today. One key obstacle impeding the development of better treatment methods is the lack of an objective measure. Since negative symptoms almost always adversely affect speech production in patients, speech dysfunction have been considered as a viable objective measure. However, researchers have mostly focused on the verbal aspects of speech, with scant attention to the non-verbal cues in speech. In this paper, we have explored non-verbal speech cues as objective measures of negative symptoms of schizophrenia. We collected an interview corpus of 54 subjects with schizophrenia and 26 healthy controls. In order to validate the non-verbal speech cues, we computed the correlation between these cues and the NSA-16 ratings assigned by expert clinicians. Significant correlations were obtained between these non-verbal speech cues and certain NSA indicators. For instance, the correlation between Turn Duration and Restricted Speech is -0.5, Response time and NSA Communication is 0.4, therefore indicating that poor communication is reflected in the objective measures, thus validating our claims. Moreover, certain NSA indices can be classified into observable and non-observable classes from the non-verbal speech cues by means of supervised classification methods. In particular the accuracy for Restricted speech quantity and Prolonged response time are 80% and 70% respectively. We were also able to classify healthy and patients using non-verbal speech features with 81.3% accuracy. | URI: | https://hdl.handle.net/10356/105913 http://hdl.handle.net/10220/48840 |
DOI: | 10.1371/journal.pone.0214314 | Schools: | School of Electrical and Electronic Engineering Lee Kong Chian School of Medicine (LKCMedicine) |
Organisations: | Institute for Media Innovation | Rights: | © 2019 Tahir et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles LKCMedicine Journal Articles |
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Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia.pdf | 1.16 MB | Adobe PDF | ![]() View/Open |
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