For dementia screening and monitoring, standardized tests play a key role in
clinical routine since they aim at minimizing subjectivity by measuring
performance on a variety of cognitive tasks. In this paper, we report on a
study that consists of a semi-standardized history taking followed by two
standardized neuropsychological tests, namely the SKT and the CERAD-NB. The
tests include basic tasks such as naming objects, learning word lists, but also
widely used tools such as the MMSE. Most of the tasks are performed verbally
and should thus be suitable for automated scoring based on transcripts. For the
first batch of 30 patients, we analyze the correlation between expert manual
evaluations and automatic evaluations based on manual and automatic
transcriptions. For both SKT and CERAD-NB, we observe high to perfect
correlations using manual transcripts; for certain tasks with lower
correlation, the automatic scoring is stricter than the human reference since
it is limited to the audio. Using automatic transcriptions, correlations drop
as expected and are related to recognition accuracy; however, we still observe
high correlations of up to 0.98 (SKT) and 0.85 (CERAD-NB). We show that using
word alternatives helps to mitigate recognition errors and subsequently
improves correlation with expert scores.

该研究通过对 30 名患者的语音转录，对比专家手动评估和自动评估之间的相关性，探讨了半标准化病史采集后进行 SKT 和 CERAD-NB 两个标准化认知测试的效果；结果表明，使用自动化转录可以得到较高的相关性，而使用词汇替换技术可以缓解识别误差，进一步提高与专家评分的相关性。