From dictations to clinical reports using machine translation
| Autor: | Nico Axtmann, Najmeh Sadoughi, Gregory Finley, Amanda L. Robinson, Mark Miller, Michael Brenndoerfer, Erik Edwards, David Suendermann-Oeft, Wael Salloum |
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| Rok vydání: | 2018 |
| Předmět: |
Parsing
Machine translation Computer science business.industry media_common.quotation_subject 02 engineering and technology computer.software_genre Punctuation Truecasing 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Host (network) computer Natural language processing media_common |
| Zdroj: | NAACL-HLT (3) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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