30, November 2025

Bridging Communication Barriers in Healthcare through Machine Learning–Based Speech and Translation Systems

VOLUME-11; ISSUE-11; NOV-2025

Author(s): 1. Rinku Kumar Gupta, 2. Dr. Mampi Devi, 3. Dr. Moromi Gogoi

Authors Affiliations:

Assam Science & Technology University

DOIs:10.2015/IJIRMF/202511022     |     Paper ID: IJIRMF202511022


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This study presents a machine learning–enabled multilingual communication system for healthcare that integrates translation, speech-to-text (STT), and text-to-speech (TTS) functionalities. The methodology involved implementing Flask-based APIs using the Google Translation library, gTTS, and Speech Recognition tools, supported by a web interface for user interaction. The system was evaluated using BLEU scores across multiple language pairs, including English–Hindi and English–Bengali, to assess translation accuracy. Results demonstrated satisfactory performance, with consistent BLEU scores confirming reliable translations. The proposed framework effectively bridges communication gaps between healthcare providers and patients, particularly in multilingual contexts. Overall, the system shows strong potential to enhance accessibility and quality of care through practical, user-friendly integration of machine learning tools in healthcare communication.

 

Machine Learning, Healthcare Communication, Speech-to-Text, Multilingual Translation

Rinku Kumar Gupta,  Dr. Mampi Devi,  Dr. Moromi Gogoi (2025); Bridging Communication Barriers in Healthcare through Machine Learning–Based Speech and Translation Systems, International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-11, Issue-11, Pp.139-145.          Available on –   https://www.ijirmf.com/

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