Latest advances in the field of natural language processing (NLP) enable new use cases for different domains, including the medical sector. In particular, transcription can be used to support automation in the nursing documentation process and give nurses more time to interact with the patients. However, different challenges including (a) data privacy, (b) local languages and dialects, and (c) domain-specific vocabulary need to be addressed. In this case study, we investigate the case of home care nursing documentation in Switzerland. We assessed different transcription tools and models, and conducted several experiments with OpenAI Whisper, involving different variations of German (i.e., dialects, foreign accent) and manually curated example texts by a domain expert of home care nursing. Our results indicate that even the used out-of-the-box model performs sufficiently well to be a good starting point for future research in the field.

翻译：自然语言处理（NLP）领域的最新进展为包括医疗部门在内的不同领域带来了新的应用场景。具体而言，转录技术可用于支持护理记录流程的自动化，从而让护士有更多时间与患者互动。然而，仍需应对包括（a）数据隐私、（b）地方语言与方言以及（c）领域特定词汇在内的诸多挑战。在本案例研究中，我们探讨了瑞士家庭护理记录的具体情况。我们评估了不同的转录工具与模型，并利用OpenAI Whisper进行了多组实验，涉及德语的多种变体（如方言、外国口音）以及由家庭护理领域专家手动整理的示例文本。我们的研究结果表明，即使直接使用未经定制的现成模型，其表现也足以成为该领域未来研究的一个良好起点。