Medical-domain Machine Translation in KConnect

Transcription

1 Medical-domain Machine Translation in KConnect Pavel Pecina Charles University, Prague Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics Czech Republic Apr 4th, 2017 QT21 workshop, Valencia, Spain This project has received funding from the European Union s Horizon 2020 research and innovation programme under grant agreement No (KConnect).

2 Outline Context of the project (Khresmoi) Project details goals and objectives Role of MT in the project Industry requirements/constraints Solutions and tools Prototypes/Demos What is still needed

3 Khresmoi Collect and make sense of biomedical information, then make it freely and easily available in several languages. FP7-ICT, No , Collaborative project Total cost: EUR ~10M, 2010/ /08 Topic: ICT Intelligent Information Management Coordinator: Henning Müller, University of Applied Sciences Western Switzerland, Sierre Consortium: 12 institutions

4 Khresmoi objectives Effective automated information extraction from (unstructured) biomedical documents Linking information extracted from unstructured biomedical texts/images to structured information in knowledge bases Support of cross-language search, including multi-lingual queries, and returning machine-translated pertinent excerpts Adaptive user interfaces to assist in formulating queries and display search results via ergonomic/interactive visualizations Automated analysis and indexing for medical images

5 Khresmoi results (MT related) MT component to allow cross-lingual search and access Based on Moses and domain-adaptation techniques Deployed as (cloud-based) web-service Translation in two modes : Translation of search queries from user languages to the documents languages (query translation) Translation of sentences from automaticaly created summaries of medical documents (summary translation) Languages: Czech, German, French English

6 KConnect a follow-up of Khresmoi Development and commercialization of cloud-based services for multilingual Semantic Annotation, Semantic Search and Machine Translation of Electronic Health Records and medical publications. H2020 project, No , Innovation action Total cost: EUR ~4M, 2015/022017/07 Topic: ICT Big data and open data innovation and take-up Coordinator: Allan Hanbury, Technical University in Viena Consortium: 10 institutions (5 from Khresmoi)

7 Consortium Academia: Technische Universitaet Wien (Austria) coordination University of Sheffield (United Kingdom) King s College London (United Kingdom) Charles University, Prague (Czech Republic) Industry: Findwise AB (Sweden) Precognox Informatikai Kft (Hungary) Ontotext AD (Bulgaria) Trip Database Ltd (United Kingdom) Health on the Net Foundation (Switzerland) Jonopkins Lan (Sweden)

8 KConnect objectives Productisation of the multilingual medical text processing tools developed in Khresmoi. Creating professional services community of companies trained to build solutions based on the KConnect Services. Development of toolkits for straightforward adaptation of the commercialised services to new languages. Adapting the services to Electronic Health Records processing, which is particularly challenging due to misspellings, neologisms, organisation-specific acronyms, etc. Languages: Hungarian, Polish, Spanish, Swedish English

9 MT Application Scenarios 1. Query translation Translation of medical/health-related search queries from a user language to the document language(s) Queries usually non-grammatical, short sequences of terms Lay-people queries vs. expert queries 2. Summary translation Sentences taken from automaticaly created abstracts of medical documents translated back to the user language Usually longer, highly informative sentences

10 Requirements, constraints Requirements Cloud-based solution, easily accessible as webservice Local instalation (hospitals) Instant response, scalable Low computation resources (local instalations) Easily (re)trainable Constraints No (very limited) domain-specific in-house training data

11 Solutions and tools Moses (phrase-based, domain adaptated) MT Monkey MT webservice architecture Eman Lite MT traninig pipeline Manually translated dev/test sets for medical domain Training data colllected and made available for WMT 17

12 MT Monkey Webservice architecture Developed at CUNI within Khresmoi Activelly extended and maintained within KConnect Scalable (see Tamchyna et al, 2013 for evaluation) Recently Dockerized

13 Eman Lite fully automated MT system training command-line and web-based interface

14 Prototypes/demos Trip database search Search in medical articles (clinical trials, research papers...) Health-on-the-Net Search Health-focused web-search engine Readability and trustablity prediction Demos

15 Trip Database Search

16 Trip Database Search

17 HON Search

18 HON Search

19 HON Search

20 HON Search (new version)

21 HON Search (new version)

22 HON Search (new version)

23 Prototypes/demos Trip database search Search in medical articles (clinical trials, research papers...) Health-on-the-Net Search Health-focused web-search engine Readability and trustablity prediction Demos

24 Issues Availability of (in-domain) training data Training data licences not clear (UMLS,MeSH, SnomedCT) Translation quality for some languages (e.g. Hungarian) Lay-people language vs. expert language