From dictations to clinical reports using machine translation
Gregory Finley, Wael Salloum, Najmeh Sadoughi, Erik Edwards, Amanda Robinson, Nico Axtmann, Michael Brenndoerfer, Mark Miller, David Suendermann-Oeft
Abstract
A typical workflow to document clinical encounters entails dictating a summary, running speech recognition, and post-processing the resulting text into a formatted letter. Post-processing entails a host of transformations including punctuation restoration, truecasing, marking sections and headers, converting dates and numerical expressions, parsing lists, etc. In conventional implementations, most of these tasks are accomplished by individual modules. We introduce a novel holistic approach to post-processing that relies on machine callytranslation. We show how this technique outperforms an alternative conventional system—even learning to correct speech recognition errors during post-processing—while being much simpler to maintain.- Anthology ID:
- N18-3015
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans - Louisiana
- Editors:
- Srinivas Bangalore, Jennifer Chu-Carroll, Yunyao Li
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 121–128
- Language:
- URL:
- https://aclanthology.org/N18-3015
- DOI:
- 10.18653/v1/N18-3015
- Cite (ACL):
- Gregory Finley, Wael Salloum, Najmeh Sadoughi, Erik Edwards, Amanda Robinson, Nico Axtmann, Michael Brenndoerfer, Mark Miller, and David Suendermann-Oeft. 2018. From dictations to clinical reports using machine translation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers), pages 121–128, New Orleans - Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- From dictations to clinical reports using machine translation (Finley et al., NAACL 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/N18-3015.pdf