Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73–0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry.

语言记忆缺陷是与精神分裂症和一般严重精神疾病相关的最严重的神经认知缺陷之一。迄今为止，它们在临床环境中的测量仅限于传统测试，这些测试允许有限的管理，并且需要大量资源来部署和评分。因此，我们开发了一种数字化动态言语记忆测试，具有自动评分功能，并通过智能设备重复进行自我管理。共有 104 名成年人参加，其中包括 25 名患有严重精神疾病的患者和 79 名健康志愿者。研究设计非常成功，92% 的提示都生成了高质量的语音录音（患者：86%，健康人：96%）。故事回忆均由人类转录和评分，使用自然语言处理转录生成的分数与人类评分相当（R = 0.83，在人与人之间的相关性 R = 0.73-0.89 范围内）。对自动语音识别生成的转录本进行评分的全自动方法产生了可比且准确的分数 (R = 0.82)，与人类转录本的分数 (R = 0.99) 具有非常高的相关性。这项研究证明了利用语音技术促进频繁评估言语记忆以用于精神病学临床监测目的的可行性。