The Joint Effects of Acoustic and Linguistic Markers for Early Identification of Mild Cognitive Impairment - Tang, Fengyi; Chen, Jun; Dodge, Hiroko H.; Zhou, Jiayu (Frontiers in Digital Health, 2022)
In recent years, behavioral markers such as spoken language and lexical preferences have been studied in the early detection of mild cognitive impairment (MCI) using conversations. While the combination of linguistic and acoustic signals has been shown to be effective in detecting MCI, they have generally been restricted to structured conversations in which the interviewee responds to fixed prompts. In this study, we propose a stratification scheme that proves to be effective in extracting quality linguistic and acoustic MCI markers in semi-structured more natural conversational settings. Using conversational data from the ongoing clinical trial, we find that the combination of linguistic and audio features achieve a mean AUC of 82.7, significantly (p-value of <0.01) out-performing linguistic-only (74.9 mean AUC) or acoustic-only (65.0 mean AUC) detections on hold-out data. Both the extracted linguistic and acoustic markers reveal notable differences in the environment and mood of MCI participants compared to those with normal cognition.