English Doctor-Patient Conversations
Start training, testing or fine-tuning your speech models with 2000 hours of English live, doctor-patient conversations. Human-generated transcriptions are available, as well as professionally annotated SOAP-structured notes. This dataset is perfect for those who are looking for instances of spontaneous speech between medical professionals and patients, for a variety of use cases such as ASR training, automated SOAP note generation, and many more!
Start training, testing or fine-tuning your speech models with 2000 hours of English live, doctor-patient conversations. Human-generated transcriptions are available, as well as professionally annotated SOAP-structured notes. This dataset is perfect for those who are looking for instances of spontaneous speech between medical professionals and patients, for a variety of use cases such as ASR training, automated SOAP note generation, and many more!
Start training, testing or fine-tuning your speech models with 2000 hours of English live, doctor-patient conversations. Human-generated transcriptions are available, as well as professionally annotated SOAP-structured notes. This dataset is perfect for those who are looking for instances of spontaneous speech between medical professionals and patients, for a variety of use cases such as ASR training, automated SOAP note generation, and many more!
Start training, testing or fine-tuning your speech models with 2000 hours of English live, doctor-patient conversations. Human-generated transcriptions are available, as well as professionally annotated SOAP-structured notes. This dataset is perfect for those who are looking for instances of spontaneous speech between medical professionals and patients, for a variety of use cases such as ASR training, automated SOAP note generation, and many more!
Dataset specs
Type
Audio
Sound quality
16kHz, 16 bit per channel
Region/Locale
EN
Amount
2K hours
Leverage
Train healthcare AI on real clinical conversations, verified by medical experts and grounded in real-world care
Use cases
Train your AI models to understand and interpret medical conversations, providing valuable insights to assist in clinical decision-making.
Train AI models to develop chatbots and virtual assistants capable of providing personalized health advice, answering medical questions, and assisting with appointment scheduling and medication reminders.
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Dataset specs
Type
Audio
Sound quality
16kHz, 16 bit per channel
Region/Locale
EN
Amount
2K hours