Towards Spoken Medical Prescription Understanding
- Resource Type
- Conference
- Authors
- Kocabiyikoglu, Ali Can; Portet, Francois; Blanchon, Herve; Babouchkine, Jean-Marc
- Source
- 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD) Speech Technology and Human-Computer Dialogue (SpeD), 2019 International Conference on. :1-8 Oct, 2019
- Subject
- Robotics and Control Systems
Signal Processing and Analysis
Drugs
Task analysis
Natural languages
Hospitals
Semantics
Point of care
Information systems
natural language understanding
spoken dialogue systems
medical computing
prescription management systems
- Language
Prescription Management Systems (PMS) have appeared in health institutions to reduce medication errors which affect several million people worldwide each year. However, practitioners must enter information manually into PMS which decreases the time devoted to care. In this paper, we propose to provide a Natural Language interface to the PMS so that practitioners can record their prescriptions orally through mobile devices at the point of care. We briefly describe the overall approach and focus on the Natural Language Understanding process which was approached through slot-filling. To deal with the paucity of data and the imbalanced class problem, we present a method to artificially generate medical prescriptions. Experiments on the artificial and a realistic dataset with several state-of-the-art NLU systems show that the method makes it possible to learn competitive NLU models and opens the way to experiments on speech corpora.