--- title: "Medical Conversations Dataset (English)" description: "It is a large-scale medical conversation dataset with 1,760 hours of audio recordings, featuring audio of medical calls (inbound/outbound), including med device promo, medical dictation,…" url: "https://unidata.pro/datasets/medical-conversations-english/" date_modified: "2026-05-12T10:09:58+03:00" language: "en-US" --- It is a large-scale medical conversation dataset with 1,760 hours of audio recordings, featuring audio of medical calls (inbound/outbound), including med device promo, medical dictation, product orders, and patient-doctor conversations, all paired with structured transcripts. This medical speech dataset includes MP3 and WAV formats with JSON and DOCX transcriptions, providing high-quality annotated data. ## Dataset Structure ### The Numbers Section **Numbered list:** - **Number:** 1760 — **Text:** Hours ### Tooltips Section **Tooltip items:** - **Name:** Speech - **Name:** Machine Learning - **Name:** Audio Processing - **Name:** Conversation Analysis - **Name:** Medical Audio ### Dataset Information **Table with data:** | Characteristic | Data | | --- | --- | | Description | Audio of medical calls (inbound/outbound), including med device promo, medical dictation, product orders, and patient-doctor conversations, with JSON transcripts | | Data types | Audio | | Tasks | Speech Recognition, Audio Classification | | Hours of audio | 1760 | | Language | English | | Call type | Med Device Promo call, Medical Dictation, Order Product, Pat-doc conversation | | Labeling | Metadata (id, start time, end time, transcription) | **Media Slider:** - **Video on Slayder:** - **Video on Slayder:** **Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1AlGsyioc-ACrsljy57sN6szBY9xTJHuV) ### Technical Specifications **Table with data:** | Characteristic | Data | | --- | --- | | Audio Format | MP3, WAV | | Transcription format | Json, docx | **Source and data collection methodology:** Source and collection methodology: Data was collected by a partner of Unidata. ### Dataset Use Cases - Slider **Industry Cards:** - **Industry:** Healthcare AI — **Title:** Training Clinical Speech Recognition Systems — **Text:** This medical conversation dataset supports training ASR models on real-world medical speech across doctor-patient conversations and clinical calls. The dataset contains annotated audio recordings with transcripts, enabling accurate recognition of medical terminology. It improves model performance in healthcare systems where precise transcription and understanding of clinical dialogues are required. - **Industry:** Digital Health & Clinical Documentation — **Title:** Automating Medical Transcription and Records — **Text:** Healthcare providers use this medical speech dataset to automate clinical documentation and generate structured health records. The dataset includes medical conversations such as dictation and consultations, helping systems convert speech into clinical notes. This reduces manual workload for medical professionals and improves efficiency in managing patient information and documentation workflows. - **Industry:** Conversational AI & Virtual Assistants — **Title:** Building Medical Dialogue Systems — **Text:** Developers apply this dialogue med dataset to train conversational agents for healthcare applications. It contains diverse medical dialogues, including patient-doctor interactions and service calls, supporting natural language understanding. These models assist with patient communication, appointment handling, and symptom guidance while adapting to real-world medical scenarios and conversational speech patterns. - **Industry:** Call Centers & Healthcare Operations — **Title:** Analyzing Medical Customer Interactions — **Text:** This medical dataset helps analyze inbound and outbound medical calls, including product orders and support requests. Organizations use it to study customer service performance, extract insights from medical conversations, and improve patient care. The dataset provides structured audio data for sentiment analysis, interaction quality monitoring, and operational optimization in healthcare call centers. ### Fact **FAQs Heading:** FAQs **List of Questions:** - **Question:** What types of annotations are provided? — **Answer:** Annotations include metadata and time-aligned transcripts, such as call ID, start time, end time, and full transcription. - **Question:** What technical formats are included in the dataset? — **Answer:** Audio is provided in MP3 and WAV formats, ensuring compatibility with standard ASR and speech processing pipelines. Transcriptions are available in both JSON and DOCX formats for flexible integration into healthcare systems. - **Question:** What types of medical conversations are included? — **Answer:** The dataset includes multiple call categories such as medical device promotion calls, medical dictation, product orders, and patient-doctor conversations. This diversity improves performance for real-world healthcare speech models and conversational AI systems. - **Question:** How was the data collected? — **Answer:** The dataset was collected by a partner of Unidata from real-world medical communication sources. - **Question:** How are Unidata datasets licensed? — **Answer:** Unidata datasets follow a dual-licensing model, where free samples are provided for evaluation and testing, and full datasets are available exclusively through purchase. - **Question:** Do Unidata datasets comply with GDPR and data protection regulations? — **Answer:** Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is sourced from legally permissible channels to ensure ethical and lawful usage. - **Question:** How are Unidata datasets stored? — **Answer:** Datasets are securely stored on AWS cloud infrastructure, ensuring high availability and scalability. Storage and management practices follow ISO 27001 and ISO 27701 standards, ensuring strong information security and privacy compliance. - **Question:** How can this medical speech dataset improve healthcare AI applications? — **Answer:** The dataset provides real conversational speech from multiple healthcare workflows, allowing AI models to better understand medical terminology, patient interactions, and clinical communication. It supports applications such as voice assistants, clinical documentation, speech analytics, and healthcare automation. [Full list of this site's AI-readable pages](https://unidata.pro/llms.txt)