Iterative LLM-based improvement for French Clinical Interview Transcription and Speaker Diarization
arXiv:2603.00086v1 Announce Type: new Abstract: Automatic speech recognition for French medical conversations remains challenging, with word error rates often exceeding 30% in spontaneous clinical speech. …
Ambre Marie (LaTIM), Thomas Bertin (DySoLab), Guillaume Dardenne (LaTIM), Gwenol\'e Quellec (LaTIM)
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