Automatic Speech Recognition for Biomedical Data in Bengali Language

Recent advancements in domain specific Automated Speech Recognition (ASR) and Large Language Models (LLM), have significantly boosted the adoption of AI in digital services across many different industries such as financial service, healthcare. In the healthcare industry in particular, integration of AI-driven solutions such as conversational chatbots, voice interactive guidance is opening new avenues to engage patients and healthcare providers ([1], [2]). Many healthcare systems in the developed world have been adopting these systems to increase patient satisfaction. One key shortcomings in this is that the majority of the developments in this domain are focused towards patients of European descent, their medical vocabularies. Many non-European languages, though spoken by millions, have seen very limited advancements. Bengali, despite being the seventh most popular language with 270 million speakers worldwide, has seen very limited progress in Bengali NLP and ASR research. This has hindered the integration of these technologies into digital health services for Bengali speakers which in turn slowed down the adoption of digital health solutions. While many European language speakers are benefiting from AI-driven services (conversational chatbot assisted) like digital appointment booking, symptom reporting before appointment and mental health support, Bengalis speakers are not able to benefit from these advancements. Bengali ASR research has seen a significant surge in recent years, fueled by the release of large public speech corpora like Google's "Large Bengali ASR training data" (LB-ASRTD).