<ul><li>Spoken Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc.</li><li>VietMed-NER is the first spoken NER dataset in the medical domain, and the largest spoken NER dataset in the world for the number of entity types.</li><li>Baseline results using various state-of-the-art pre-trained models show that pre-trained multilingual models generally outperform monolingual models on reference text and ASR output.</li><li>The dataset can be utilized for text NER in the medical domain in other languages by translating the transcripts.</li></ul>

Medical Spoken Named Entity Recognition

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