Pronoun use in preclinical and early stages of Alzheimer's dementia

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Computer Speech and Language Pub Date : 2023-10-12 DOI:10.1016/j.csl.2023.101573
Dagmar Bittner , Claudia Frankenberg , Johannes Schröder
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引用次数: 1

Abstract

The present study aims at improving the predictive power of the use of pronouns in computational modeling of the risk of Alzheimer's dementia (AD) by (i) further determining the onset of increased pronoun use in AD and (ii) providing insights into the linguistic contexts affected by the increase early on. Pronoun use was compared longitudinally between subjects who either stayed cognitively intact (CTR-group, n = 5) or who had developed AD upon follow-up after 10–12 years (AD-group, n = 5). Data were taken from semi-structured biographical interviews, which stem from the Interdisciplinary Longitudinal Study on Adult Development and Aging (ILSE). The first interview (baseline) was conducted when all participants were still cognitively healthy. Analyses concerned the proportional distribution of 12 pronoun types and linguistic contexts of increased use. Already at baseline, the AD-group produced a significantly higher proportion of D-pronouns (der, die, das, etc.) than the CTR-group. The increase in D-pronouns did not affect linguistic contexts favoring the use of personal pronouns. Instead, we found a significantly higher proportion of D-pronouns referring to family members and a significantly higher proportion of personal pronouns referring to non-family humans in the AD-group than in the CTR-group. Our results suggest that the predictive power of the use of pronouns can be significantly improved in computational modeling of the risk of AD by assessing language material that induces the use of pronouns in linguistic contexts affected by the increase.

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Pronoun在阿尔茨海默病痴呆症临床前和早期的应用
本研究旨在通过(i)进一步确定AD中代词使用增加的开始,以及(ii)深入了解早期受代词使用增加影响的语言环境,提高代词在阿尔茨海默病(AD)风险计算建模中的预测能力。在保持认知完整的受试者(CTR组,n=5)或在10-12年后随访时患上AD(AD组,n=5)之间,对代词的使用进行纵向比较。数据来自半结构化的传记访谈,这些访谈源于成人发展与衰老跨学科纵向研究(ILSE)。第一次访谈(基线)是在所有参与者仍然认知健康的情况下进行的。分析涉及12种代词类型的比例分布和增加使用的语境。在基线时,AD组产生的D代词(der、die、das等)比例明显高于CTR组。D代词的增加并没有影响到有利于使用人称代词的语境。相反,我们发现AD组中提及家庭成员的D代词比例显著高于CTR组,提及非家庭人类的人称代词比例显著较高。我们的研究结果表明,在AD风险的计算建模中,通过评估在受增加影响的语言环境中诱发代词使用的语言材料,可以显著提高代词使用的预测能力。
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来源期刊
Computer Speech and Language
Computer Speech and Language 工程技术-计算机:人工智能
CiteScore
11.30
自引率
4.70%
发文量
80
审稿时长
22.9 weeks
期刊介绍: Computer Speech & Language publishes reports of original research related to the recognition, understanding, production, coding and mining of speech and language. The speech and language sciences have a long history, but it is only relatively recently that large-scale implementation of and experimentation with complex models of speech and language processing has become feasible. Such research is often carried out somewhat separately by practitioners of artificial intelligence, computer science, electronic engineering, information retrieval, linguistics, phonetics, or psychology.
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