This project explores how AI can help understand bilingual doctor–patient conversations and automatically generate accurate medical documentation. It has the potential to improve healthcare accessibility and reduce documentation workload for clinicians serving multilingual populations. We have already build 280 hours speech corpus containing code-switched Kazakh-Russian medical data. We now collecting an additional 100 hours of simulated doctor and patient conversations to improve model performance.
Tags: Basic Programming, Python, Artificial Intelligence, Machine Learning, Natural Language Processing, Data Science, All Years