Revolutionizing Radiological Analysis: The Future of French Language Automatic Speech Recognition in Healthcare-Reference-Cited by-同舟云学术

Revolutionizing Radiological Analysis: The Future of French Language Automatic Speech Recognition in Healthcare

Published:2024-04-25 Issue:9 Volume:14 Page:895
ISSN:2075-4418
Container-title:Diagnostics
language:en
Short-container-title:Diagnostics

Author:

Jelassi Mariem¹²^ORCID,Jemai Oumaima²³,Demongeot Jacques⁴^ORCID

Affiliation:

1. RIADI Laboratory, Ecole Nationale des Sciences de l’Informatique (ENSI), Manouba University, La Manouba 2010, Tunisia

2. Health Tech Innovation Systems Inc., ENSI Innovation Hub, La Manouba 2010, Tunisia

3. Ecole Supérieure des Communications de Tunis (SUP’COM), Carthage University, Ariana 2083, Tunisia

4. AGEIS Laboratory, Faculté de Médecine, Université Grenoble Alpes (UGA), 38700 La Tronche, France

Abstract

This study introduces a specialized Automatic Speech Recognition (ASR) system, leveraging the Whisper Large-v2 model, specifically adapted for radiological applications in the French language. The methodology focused on adapting the model to accurately transcribe medical terminology and diverse accents within the French language context, achieving a notable Word Error Rate (WER) of 17.121%. This research involved extensive data collection and preprocessing, utilizing a wide range of French medical audio content. The results demonstrate the system’s effectiveness in transcribing complex radiological data, underscoring its potential to enhance medical documentation efficiency in French-speaking clinical settings. The discussion extends to the broader implications of this technology in healthcare, including its potential integration with electronic health records (EHRs) and its utility in medical education. This study also explores future research directions, such as tailoring ASR systems to specific medical specialties and languages. Overall, this research contributes significantly to the field of medical ASR systems, presenting a robust tool for radiological transcription in the French language and paving the way for advanced technology-enhanced healthcare solutions.

Publisher

MDPI AG

Link

https://www.mdpi.com/2075-4418/14/9/895/pdf

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