Understanding Cohesion in Writings and Speech of Schizophrenia Patients

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)(2019)

引用 0|浏览31
暂无评分
摘要
Schizophrenia is one of the mental disorders that impacts a person's thinking, speech, and actions. It can reduce a person's ability to process auditory information and make decisions. Analyzing this disorder correctly is important because it might help with different ways of reducing its negative effects on its patients. Linguists and psychiatrists have been investigating language impairments and speech disorder in people with schizophrenia disorder which can be challenging. In this study, we attempt to address this issue by analyzing linguistic features i.e. cohesion in the writings and speech scripts of schizophrenia patients. Our results show that using referential cohesion with text easability or situation model features provides the best performance for speech whereas for writing dataset, readability or a combination of situation model and readability yield the best performance.
更多
查看译文
关键词
Schizophrenia,Machine-Learning-Algorithms,Binary-Classification,Coherence,Cohesion,Coh-Metrix
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要