How translators work in real life: SCATE observations. Frieda Steurs Iulianna van der Lek-Ciudin Tom Vanallemeersch

Transcription

1 How translators work in real life: SCATE observations Frieda Steurs Iulianna van der Lek-Ciudin Tom Vanallemeersch

2 What & Why Improve translation efficiency and consistency Underexploited translation resources Poor integration of speech recognition Overloaded interfaces

3 Consortium March February 2018 Centre for Computational Linguistics, University of Leuven Industrial Advisory Committee

4 Today s focus

5 Methods Survey Contextual inquiries

6 Methods Survey: Dec 2014 Feb questions 187 complete responses (75% from EU) 73 % freelance translators 25 % in-house translators Few terminologists, interpreters, project managers, post-editors Contextual Inquiries: Nov June professionals at their workplaces (BE, NL, LU) Semi-structured interviews, observations, think-aloud, post-interviews

7 Whom did we observe? Organization type Language pairs Translation experience Domains of expertise Main TEnT Experience with TEnT Small translation agency Medium-size translation/interpreting agency Public institution Freelance EN-NL/NL-EN, FR-NL, EN-FR, EN-RO 2-5 years vs. 5 + years Legal, ICT, Medical, Marketing Trados Studio 2014, Trados Studio 2011, Trados Workbench, Déjà Vu X3, memoq 2014, Wordbee <1 year (2) vs. 5+ years

8 Main findings and implications Needs and shortcomings of tools Observation of terminological strategies

9 Translators Linguistic Resources Resource State-of-the-art Opportunities Translation Memories Heavily used Concordance, term look-up features, term extraction Term extraction rarely used Alignment No support for comparable corpora (possible to upload monolingual documents for reference) Syntactic concordance Bilingual/multilingual term extraction More focus on monolingual corpora Features to compile and query comparable corpora Online Translation Memories Perform look-up during translation Automatic insertion Concordance searches Moderate-low quality control More advanced filtering techniques QA tools

10 Translators Linguistic Resources Resource State-of-the-art Opportunities Local term bases Usage is still low (SCATE survey -> 52%) Automatic term recognition Basic categories TBX not adopted by all tool developers Users prefer to exchange data in CSV, Excel Online term banks Online dictionaries, search engines Perform look-up (exact/fuzzy) during translation Consulted either online or via a WebSearch feature in CAT Improve usability More flexibility and customization to suit users with different needs A unified interface for online/local term bases Support for ontologies Advanced pre-filtering, techniques, better look-up interfaces Concordance-like searches directly from the translation editor

11 Translators Linguistic Resources Resource State-of-the-art Opportunities Machine Translation Usage is still low (SCATE survey 27%) Consulted online Via API in CAT Segment assembly (DejaVu, memoq) Autocompletion suggestions (SDL Trados) Adaptive MT (MateCat, Lilt) Improve confidence estimation Interfaces for postediting Train own MT engine with own TMs, TBs

12 187 survey participants 139 perform terminology activities Term collection Manually (88%) Semi-automatically via term extraction programs (22%) Term storage CAT TB (52%) Most frequent form/canonical form MS Excel (43%) The language equivalents (56%) MS Word (27%) Term research Online resources (94%) Personal resources (85%) Client s resources (64%) SCATE Users survey

13 Search engines Most used online terminology resources Online dictionaries Term banks Monolingual Corpora Parallel corpora Oxford IATE Eur-lex Linguee Google Bing Proz.com Van Dale TermWiki Search TermCoord glossary links Termium Plus EuroTerm Bank FAOTERM WTOTERM Global webbased English British National corpus Corpus of contempo rary AE Europarl Glosbe TAUS Search SCATE Users survey

14 Reasons for NOT managing terminology No knowledge about terminology management theory and principles It is the responsibility of somebody else It has no added value It is a time-consuming task Term bases are complex Reliance on the translation memories SCATE Users survey

15 Systematic terminology management Collect terms and concepts from global field Construct a concept system Create well-structured definitions Create term entries In-house translation departments of large organizations Ad-hoc terminology management Identify terms in isolated contexts Create initial term entries Add definition, context. Adapted from Handbook of Terminology Management Vol 1. Medium & small LSPs, freelancers

16 Institution In-house translation departments Translators / terminologists In-house terminology coordination Systematic and ad-hoc terminology management Term extraction not a standard practice! Terminology strategies Terminology tools IATE database Eur-Lex Quest Metasearch (Bilingual) Euramis Concordance DGT Vista Electronic dictionaries, glossaries Term extraction tools: SynchroTerm, SDL MultiTerm Extract, TermTreffer Translation tools SDL Trados Studio In-house MT Voice recognition External corpus query tools, e.g. TextStat 16

17 Terminology strategies Adapted after TermCoord documentation

18 Terminology strategies Proactive terminology management Preparation of TermFolders for important legislative procedures: Desktop research Manual collection of web links and relevant documents Manual identification and extraction of term candidates.

19 Terminology strategies Time-consuming No GlobalSearch DIY Corpora tools? SCATE?

20 Terminology strategies Small and medium-size LSPs, freelancers Mainly ad-hoc, basic terminology management due to: o o o o o Time pressure Lack of financial compensation Over-reliance on translation memories A general lack of knowledge and awareness of the benefits of terminology management Not familiar with corpus compilation and query tools

21 Ad-hoc terminology strategies during translation Identify problem LGP, terminology, phraseology, names of entities, typography/punctuation Highlight or copy/paste SL term Search for a solution Local resources: Concordance, Term Look-up, Find & Replace, Global search Online resources via WebSeach or other integrated widgets MT via plugins, if available & allowed Online resources: Google -> Top hits (Bookmark link?) Contact client via or an online query spreadsheet Contact subject matter experts Insert translation One click Copy/paste Save terms Term base / Excel

22 Implications For translators, project managers, terminologists, interpreters, translators educators: Basic knowledge of terminology theory and practice Terminology management tools Preparation of glossaries before the start of the project with the help of: Corpus compilation and query tools (BootCat, AntConc, SketchEngine) Term extraction tools (SynchroTerm, Similis) More focus on comparable corpora

23 Implications For software developers: Focus more on usability and personalization Unified interfaces between local and online resources More sophisticated search functionalities Integrate online resources that are actually used by the users More focus on comparable corpora

24 SCATE approach

25 SCATE research Improvement of bilingual and multilingual term extraction techniques from comparable corpora Integration of a syntactic concordancer in parallel corpora: e.g. Poly-Gretel

26 Multilingual term extraction from comparable corpora A gold standard for Automatic Terminology Extraction Compilation Annotation Evaluation # words Hartfailure Wind energy Corruption Corruption (parallel) English French Dutch

27 Annotation: 4 labels (Term, Common Term, Out of Domain Term and Named Entity) with elaborate and practical guidelines Evaluation: inter-annotator agreement between 3 annotators after 2 iterations (av. f-score = 0,895; av. Cohen s kappa = 0.927) Future work: linking the annotations in the comparable medical corpus across all 3 languages A Gold Standard for Automatic Terminology Extraction

28 Bilingual lexicon induction from comparable corpora Comparable corpora Cross-lingual semantic word representations Bilingual lexicon Techniques for extracting word representations: o o o multilingual topic models multilingual word embedding models Best results character-level representations

29 Poly-Gretel Bilingual syntactic concordancer Query parallel corpora Available online at: Target audience: Computer-assisted language learning (CALL) Translators Translation studies and comparative linguistics

30 Poly-Gretel EN noun + report NL verslag + prep + noun Example query:

31 Poly-Gretel EN noun + report NL verslag + prep + noun EN-NL constituents are automatically aligned

32 Poly-Gretel EN noun + report NL noun Example query: Many compounds are possible

33 More about SCATE