ICASSP 2016accepted0 citations

Non-verbal speech analysis of interviews with schizophrenic patients

Yasir Tahir, Debsubhra Chakraborty, Justin Dauwels, Nadia Magnenat-Thalmann, Daniel Thalmann, Jimmy Lee

Abstract

Negative symptoms in schizophrenia are associated with significant burden and functional impairment, especially speech production. In clinical practice today, there are no robust treatments for negative symptoms and one obstacle surrounding its research is the lack of an objective measure. To this end, we explore non-verbal speech cues as objective measures. Specifically, we extract these cues while schizophrenic patients are interviewed by psychologists. We have analyzed interviews of 15 patients who were enrolled in an observational study on the effectiveness of Cognitive Remediation Therapy (CRT). The subject (undergoing CRT) and control group (not undergoing CRT) contains 8 and 7 individuals respectively. The patients were recorded during three sessions while being evaluated for negative symptoms over a 12-week follow-up period. In order to validate the non-verbal speech cues, we computed their correlation with the Negative Symptom Assessment (NSA-16). Our results suggest a strong correlation between certain measures of the two rating sets. Supervised prediction of the subjective ratings from the non-verbal speech features with leave-one-person-out cross-validation has reasonable accuracy of 53-80%. Furthermore, the non-verbal cues can be used to reliably distinguish between the subjects and controls, as supervised learning methods can classify the two groups with 80-93% accuracy.

BibTeX
@inproceedings{icassp2016_nonverbalspeecha,
  title = {Non-verbal speech analysis of interviews with schizophrenic patients},
  author = {Yasir Tahir and Debsubhra Chakraborty and Justin Dauwels and Nadia Magnenat-Thalmann and Daniel Thalmann and Jimmy Lee},
  booktitle = {ICASSP 2016},
  year = {2016}
}