Medical Spoken Named Entity Recognition

arXiv (Cornell University)

Abstract

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 distinct types. Furthermore, we present baseline results using various state-of-the-art pre-trained models: encoder-only and sequence-to-sequence; and conduct quantitative and qualitative error analysis. We found that pre-trained multilingual models generally outperform monolingual models on reference text and ASR output and encoders outperform sequence-to-sequence models in NER tasks. By translating the transcripts, the dataset can also be utilised for text NER in the medical domain in other languages than Vietnamese. All code, data and models are publicly available: https://github.com/leduckhai/MultiMed/tree/master/VietMed-NER.

Authors 7

1. Khai Le-Duc corresponding

   University of Toronto · University Health Network

   Affiliation as printed

   University Health Network , Canada

   University of Toronto , Canada

2. David Thulke Aachen Machine Learning and Human Language Technology Group

   RWTH Aachen University

   Affiliation as printed

   AppTek GmbH , Germany

   Machine Learning and Human Language Technology Group , RWTH Aachen University , Germany

3. Hung-Phong Tran

   Hanoi University of Science and Technology · Trường Đại học Khoa học và Công nghệ Hà Nội

   Affiliation as printed

   Hanoi University of Science and Technology , Vietnam

4. Long Vo-Dang

   University of Cincinnati

   Affiliation as printed

   Train Dev Test All Total Uni . Total Uni . Total Uni. Total Uni

   University of Cincinnati , United States

5. Khai-Nguyen Nguyen

   William & Mary

   Affiliation as printed

   College of William and Mary , United States

6. Truong-Son Hy

   University of Alabama at Birmingham

   Affiliation as printed

   University of Alabama at Birmingham , United States

7. Ralf Schlüter