Dataset for Automated Medical Transcription

We generated this dataset to train a machine learning model for automatically generating psychiatric case notes from doctor-patient conversations. Since, we didn't have access to real doctor-patient conversations, we used transcripts from two different sources to generate audio recordings of enacted conversations between a doctor and a patient. We employed eight students who worked in pairs to generate these recordings. Six of the transcripts that we used to produce this recordings were hand-written by Cheryl Bristow and rest of the transcripts were adapted from Alexander Street which were generated from real doctor-patient conversations. Our study requires recording the doctor and the patient(s) in seperate channels which is the primary reason behind generating our own audio recordings of the conversations. We used Google Cloud Speech-To-Text API to transcribe the enacted recordings. These newly generated transcripts are auto-generated entirely using AI powered automatic speech recognition whereas the source transcripts are either hand-written or fine-tuned by human transcribers (transcripts from Alexander Street). We provided the generated transcripts back to the students and asked them to write case notes. The students worked independently using a software that we developed earlier for this purpose. The students had past experience of writing case notes and we let the students write case notes as they practiced without any training or instructions from us. <strong>NOTE:</strong> Audio recordings are not included in Zenodo due to large file size but they are available in the GitHub repository.本数据集旨在训练可基于医患对话自动生成精神科病历的机器学习模型。由于无法获取真实医患对话转录稿，我们采用两类来源的转录文本，生成了医患角色扮演对话的音频录制内容。我们招募8名学生以双人搭档的形式完成上述音频录制。本次制作音频所用的转录稿中，6份由Cheryl Bristow手写完成，剩余转录稿改编自Alexander Street平台上源自真实医患对话的原始转录稿。本研究要求将医生与患者（们）的音频信号分轨录制，这也是我们自行生成对话音频的核心原因。我们借助谷歌云语音转文字（Google Cloud Speech-To-Text）API，对生成的角色扮演对话音频进行转写。本次新生成的转录稿完全由AI驱动的自动语音识别技术生成，而源转录稿则要么为手写原稿，要么由人工转录员对Alexander Street来源的转录稿进行过微调优化。我们将生成的转录稿反馈给学生，并要求其据此撰写病历。学生们通过我们此前专为该项目开发的软件独立完成病历撰写。这些学生均具备既往撰写病历的经验，且我们未提供任何培训或指导，允许其按照日常实践方式完成撰写工作。<strong>备注：</strong>由于文件体积过大，音频录制内容未收录于Zenodo平台，但可在GitHub仓库中获取。