A "Verbal Thermometer" for Assessing Neurodegenerative Disease: Automated Measurement of Pronoun and Verb Ratio from Speech.

42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20(2020)

引用 3|浏览6
暂无评分
摘要
Clinicians often use speech to characterize neurodegenerative disorders. Such characterizations require clinical judgment, which is subjective and can require extensive training. Quantitative Production Analysis (QPA) can be used to obtain objective quantifiable assessments of patient functioning. However, such human-based analyses of speech are costly and time consuming. Inexpensive off-the-shelf technologies such as speech recognition and part of speech taggers may avoid these problems. This study evaluates the ability of an automatic speech to text transcription system and a part of speech tagger to assist with measuring pronoun and verb ratios, measures based on QPA. Five participant groups provided spontaneous speech samples. One group consisted of healthy controls, while the remaining groups represented four subtypes of frontotemporal dementia. Findings indicated measurement of pronoun and verb ratio was robust despite errors introduced by automatic transcription and the tagger and despite these off-the-shelf products not having been trained on the language obtained from speech of the included population.
更多
查看译文
关键词
Frontotemporal Dementia,Humans,Neurodegenerative Diseases,Pick Disease of the Brain,Speech,Thermometers
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