leduckhai/VietMed-NER
Medical Spoken Named Entity Recognition (NAACL 2025) Description: Spoken Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc. In this work, we present VietMed-NER - the first spoken NER dataset in the medical domain. To our knowledge, our Vietnamese real-world dataset is the largest spoken NER dataset in the world regarding the number of entity types, featuring 18… See the full description on the dataset page: https://huggingface.co/datasets/leduckhai/VietMed-NER.
| Author / organization | leduckhai |
|---|---|
| Downloads | 261 (as reported by Hugging Face) |
| Likes | 9 |
| Created | 18 June 2024 |
| Last updated at source | 5 April 2025 |
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261 now (+2 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: Medical Spoken Named Entity Recognition (NAACL 2025) Description: Spoken Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc. In this work, we pre → Medical Spoken Named Entity Recognition (NAACL 2025) Description: Spoken Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc. In this work, we pre
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