Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization

5 Steps

1. 1

   Define Conversation Parameters: Outline the specific scenario for your synthetic conversation. Include details like patient demographics, chief complaint, medical history, doctor's specialty, and the desired length of the interaction. This provides context for script generation.

2. 2

   Generate Dialogue Scripts: Use a Large Language Model (LLM) to generate realistic doctor-patient conversation scripts based on the parameters defined in Step 1. Ensure the script includes natural turns, medical terminology, and appropriate emotional tones.

3. 3

   Synthesize Audio from Scripts: Convert the generated dialogue scripts into audio files using a Text-to-Speech (TTS) model. Assign distinct synthetic voices for the doctor and patient to simulate a real conversation. Consider using open-source TTS libraries or cloud-based services.

4. 4

   Introduce Realism and Variation: Enhance the synthetic audio by adding realistic elements. This includes introducing slight pauses, varying speech rates, adding background ambient noise (e.g., hospital sounds, room tone), and subtle intonation changes to mimic natural human speech.

5. 5

   Evaluate and Iterate: Assess the quality, realism, and medical accuracy of the generated synthetic conversations and audio. Use both automated metrics (e.g., speech recognition accuracy on synthetic audio) and human review. Refine your parameters, LLM prompts, and TTS settings based on feedback to improve data quality.