School of English, University of Sheffield , Sheffield, UK.
Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield , Sheffield, UK.
Clin Linguist Phon. 2021 Mar 4;35(3):237-252. doi: 10.1080/02699206.2020.1777586. Epub 2020 Jun 19.
The diagnosis of Mild Cognitive Impairment (MCI) characterises patients at risk of dementia and may provide an opportunity for disease-modifying interventions. Identifying persons with MCI (PwMCI) from adults of a similar age without cognitive complaints is a significant challenge. The main aims of this study were to determine whether generic speech differences were evident between PwMCI and healthy controls (HC), whether such differences were identifiable in responses to recent or remote memory questions, and to determine which speech variables showed the clearest between-group differences. This study analysed recordings of 8 PwMCI (5 females, 3 males) and 14 HC of a similar age (8 females, 6 males). Participants were recorded interacting with an intelligent virtual agent: a computer-generated talking head on a computer screen which asks pre-recorded questions when prompted by the interviewee through pressing the next key on a computer keyboard. Responses to recent and remote memory questions were analysed. Mann-Whitney U tests were used to test for statistically significant differences between PwMCI and HC on each of 12 speech variables, relating to temporal characteristics, number of words produced and pitch. It was found that compared to HC, PwMCI produce speech for less time and in shorter chunks, they pause more often and for longer, take longer to begin speaking and produce fewer words in their answers. It was also found that the PwMCI and HC were more alike when responding to remote memory questions than when responding to recent memory questions. These findings show great promise and suggest that detailed speech analysis can make an important contribution to diagnostic and stratification systems in patients with memory complaints.
轻度认知障碍（MCI）的诊断特征为痴呆风险患者，并可能为疾病修饰干预提供机会。从无认知主诉的相似年龄的成年人中识别出 MCI 患者（PwMCI）是一项重大挑战。本研究的主要目的是确定 PwMCI 与健康对照者（HC）之间是否存在一般言语差异，这些差异是否可在对近期或远期记忆问题的回答中识别，以及确定哪些言语变量在组间差异中表现最明显。本研究分析了 8 名 PwMCI（5 名女性，3 名男性）和 14 名年龄相似的 HC（8 名女性，6 名男性）的录音。参与者与智能虚拟代理进行交互：计算机屏幕上的计算机生成的会说话的头像，当被访者通过按下计算机键盘上的下一个键提示时，会询问预先录制的问题。对近期和远期记忆问题的回答进行了分析。使用 Mann-Whitney U 检验测试了 12 项与时间特征、生成的单词数量和音高等相关的言语变量在 PwMCI 和 HC 之间的统计学显著差异。与 HC 相比，PwMCI 的言语持续时间和片段更短，停顿更频繁且持续时间更长，开始说话的时间更长，回答中的单词更少。还发现，与回答近期记忆问题相比，PwMCI 和 HC 在回答远期记忆问题时更为相似。这些发现显示出巨大的潜力，并表明详细的言语分析可以为有记忆主诉的患者的诊断和分层系统做出重要贡献。
