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New Bengali telemedicine dataset DocTalkBN released for medical NLP research

Researchers have introduced DocTalkBN, a new dataset comprising over 557 hours of expert telemedicine conversations in Bengali. This multimodal dataset includes paired audio and text, capturing 1,515 multi-turn patient calls and 10,274 question-answer exchanges across 26 medical specialties. Unlike datasets derived from written content or synthetic data, DocTalkBN preserves the natural flow and spoken characteristics of authentic medical interactions in a low-resource language. The dataset also includes benchmarks for three downstream tasks: medical triage classification, advice safety evaluation, and medical named entity recognition, with initial evaluations of various large language models. AI

IMPACT This dataset could advance the development of more culturally grounded and reliable medical NLP systems for low-resource languages.

RANK_REASON The item describes a new dataset and benchmark for NLP research, released on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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New Bengali telemedicine dataset DocTalkBN released for medical NLP research

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The item describes a new dataset and benchmark for NLP research, released on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Anik Saha, Fahmida Sultana Naznin, Sadatul Islam Sadi, Ananya Shahrin Promi, Wahid Al Azad Navid, Rifat Shahriyar ·

    DocTalkBN: A Novel Dataset of Expert Telemedicine Conversations in Bengali

    arXiv:2608.27110v1 Announce Type: new Abstract: Reliable medical conversational AI requires authentic expert--patient interaction data, yet such datasets remain scarce, especially for low-resource languages such as Bengali. We present DocTalkBN, a large-scale multimodal dataset o…