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Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia

机译:非言语提示作为精神分裂症患者阴性症状的客观测量

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摘要

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.
机译:精神分裂症的阴性症状伴随着巨大的负担,在当今的临床实践中几乎没有或没有强有力的治疗方法。缺乏更好的治疗方法是阻碍发展更好的治疗方法的主要障碍。由于负面症状几乎总是对患者的言语产生不利影响,因此言语功能障碍已被认为是可行的客观措施。然而,研究人员大多集中在言语的言语方面,而很少注意言语的非言语暗示。在本文中,我们探索了非言语提示作为精神分裂症消极症状的客观度量。我们收集了54位精神分裂症患者和26位健康对照者的访谈语料库。为了验证非语言语音提示,我们计算了这些提示与专家临床医生分配的NSA-16评分之间的相关性。在这些非语言语音提示和某些NSA指标之间获得了显着的相关性。例如,转弯时长和受限语音之间的相关性是-0.5,响应时间和NSA沟通之间的相关性是0.4,因此表明客观衡量标准中反映了沟通不佳,从而验证了我们的主张。此外,可以通过监督分类方法将某些NSA索引从非语言语音提示中分为可观察和不可观察类别。特别地,限制语音量和延长响应时间的准确度分别为80%和70%。我们还能够使用非语言语音功能对健康人和患者进行分类,准确率达到81.3%。

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