leduckhai/MultiMed
[LREC-COLING 2024 (Oral), Interspeech 2024 (Oral), NAACL 2025, ACL 2025, EMNLP 2025] A Series of Multilingual Multitask Medical Speech Processing
This project offers tools to understand medical conversations by converting spoken language into text, extracting key information, and summarizing discussions. It takes audio recordings of medical speech, such as doctor-patient dialogues, and outputs detailed transcripts, identified medical terms, and concise summaries. Medical professionals, researchers studying medical communication, and healthcare administrators can use this to streamline documentation and analyze interactions.
373 stars.
Use this if you need to accurately transcribe medical conversations, identify specific medical terms within speech, or generate summaries from spoken medical interactions across multiple languages.
Not ideal if your primary need is for general domain speech recognition or summarization outside of a medical context.
Stars
373
Forks
36
Language
Python
License
—
Category
Last pushed
Dec 31, 2025
Commits (30d)
0
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