Judith Klein


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How STAR Transit NXT can help translators measure and increase their MT post-editing efficiency
Julian Hamm | Judith Klein
Proceedings of the 24th Annual Conference of the European Association for Machine Translation

As machine translation (MT) is being more tightly integrated into modern CAT-based translation workflows, measuring and increasing MT efficiency has become one of the main concerns of LSPs and companies trying to optimise their processes in terms of quality and performance. When it comes to measur-ing MT efficiency, STAR’s CAT tool Transit NXT offers post-editing distance (PED) and MT error categorisation as two core features of Transit’s compre-hensive QA module. With DeepL glossa-ry integration and MT confidence scores, translators will also have access to two new features which can help them in-crease their MT post-editing efficiency.


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Background Search for Terminology in STAR MT Translate
Giorgio Bernardinello | Judith Klein
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

When interested in an internal web ap-plication for MT, corporate customers always ask how reliable terminology will be in their translations. Coherent vocabulary is crucial in many aspects of corporate translations, such as doc-umentation or marketing. The main goal every MT provider would like to achieve is to fully integrate the cus-tomer’s terminology into the model, so that the result does not need to be edit-ed, but this is still not always guaran-teed. Besides, a web application like STAR MT Translate allows our cus-tomers to use – integrated within the same page – different generic MT pro-viders which were not trained with customer-specific data. So, as a prag-matic approach, we decided to in-crease the level of integration between WebTerm and STAR MT Translate, adding to the latter more terminological information, with which the user can post-edit the translation if needed.


Use MT to Simplify and Speed Up Your Alignment for TM Creation
Judith Klein
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)

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Let MT simplify and speed up your Alignment for TM creation
Judith Klein | Giorgio Bernardinello
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

Large quantities of multilingual legal documents are waiting to be regularly aligned and used for future translations. For reasons of time, effort and cost, manual alignment is not an option. Automatically aligned segments are suitable for concordance search but are unreliable for fuzzy search and pretranslation. MT-based alignment could be the key to improving the results.


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Smart Pre- and Post-Processing for STAR MT Translate
Judith Klein
Proceedings of the 21st Annual Conference of the European Association for Machine Translation

After many successful experiments it has become evident that smart pre- and post-processing can significantly improve the output of neural machine translation. Therefore, various generic and language-specific processes are applied to the training corpus, the user input and the MT output for STAR MT Translate.


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Natural Language Dialogue Service for Appointment Scheduling Agents
Stephan Busemann | Thierry Declerck | Abdel Kader Diagne | Luca Dini | Judith Klein | Sven Schmeier
Fifth Conference on Applied Natural Language Processing

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Semantic Tagging and NLP Applications
Thierry Declerck | Judith Klein
Tagging Text with Lexical Semantics: Why, What, and How?


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TSNLP - Test Suites for Natural Language Processing
Sabine Lehmann | Stephan Oepen | Sylvie Regnier-Prost | Klaus Netter | Veronika Lux | Judith Klein | Kirsten Falkedal | Frederik Fouvry | Dominique Estival | Eva Dauphin | Herve Compagnion | Judith Baur | Lorna Balkan | Doug Arnold
COLING 1996 Volume 2: The 16th International Conference on Computational Linguistics