Institute for Media Innovation, Nanyang Technological University, Singapore, Singapore.
Institute of Mental Health, Singapore, Singapore.
PLoS One. 2019 Apr 9;14(4):e0214314. doi: 10.1371/journal.pone.0214314. eCollection 2019.
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.
精神分裂症的阴性症状与显著的负担有关,在当今的临床实践中几乎没有有效的治疗方法。阻碍更好的治疗方法发展的一个关键障碍是缺乏客观的衡量标准。由于阴性症状几乎总是对患者的言语产生负面影响,言语功能障碍已被认为是一种可行的客观衡量标准。然而,研究人员大多关注言语的口头方面,而对言语中的非言语线索关注甚少。在本文中,我们探讨了非言语言语线索作为精神分裂症阴性症状的客观衡量标准。我们收集了一个由 54 名精神分裂症患者和 26 名健康对照者组成的访谈语料库。为了验证非言语言语线索,我们计算了这些线索与专家临床医生分配的 NSA-16 评分之间的相关性。这些非言语言语线索与某些 NSA 指标之间存在显著相关性。例如,停顿持续时间和受限性言语之间的相关性为-0.5,反应时间和 NSA 交流之间的相关性为 0.4,这表明较差的交流反映在客观测量中,从而验证了我们的观点。此外,某些 NSA 指标可以通过监督分类方法从非言语言语线索中分为可观察和不可观察的类别。特别是,受限性言语数量和延长的反应时间的准确率分别为 80%和 70%。我们还能够使用非言语言语特征以 81.3%的准确率对健康人和患者进行分类。