Automatic Speech Recognition for Biomedical Data in Bengali Language

TL;DR

This paper develops a Bengali biomedical ASR system tailored for medical terminology and dialects, trained on a 46-hour corpus to enhance healthcare accessibility for non-technical users.

Contribution

It introduces a domain-specific Bengali biomedical ASR system with dialectal considerations, filling a gap in healthcare speech recognition technology.

Findings

Achieved promising recognition accuracy on Bengali medical terms

Successfully trained and evaluated on a 46-hour corpus

Demonstrated potential for deployment in digital health applications

Abstract

This paper presents the development of a prototype Automatic Speech Recognition (ASR) system specifically designed for Bengali biomedical data. Recent advancements in Bengali ASR are encouraging, but a lack of domain-specific data limits the creation of practical healthcare ASR models. This project bridges this gap by developing an ASR system tailored for Bengali medical terms like symptoms, severity levels, and diseases, encompassing two major dialects: Bengali and Sylheti. We train and evaluate two popular ASR frameworks on a comprehensive 46-hour Bengali medical corpus. Our core objective is to create deployable health-domain ASR systems for digital health applications, ultimately increasing accessibility for non-technical users in the healthcare sector.