Automatic Speech Recognition for Biomedical Data in Bengali Language
This addresses the problem of limited healthcare ASR accessibility for Bengali speakers, but it is incremental as it applies existing methods to new data.
The paper tackled the lack of domain-specific ASR systems for Bengali biomedical data by developing a prototype tailored for medical terms, achieving results on a 46-hour corpus.
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.