Vivien Macketanz
Vivien Macketanz
Verified email at dfki.de
Title
Cited by
Cited by
Year
CoNLL 2018 shared task: Multilingual parsing from raw text to universal dependencies
D Zeman, J Hajic, M Popel, M Potthast, M Straka, F Ginter, J Nivre, ...
Proceedings of the CoNLL 2018 Shared Task: Multilingual parsing from raw …, 2018
2792018
Universal Dependencies 1.2
J Nivre, Ž Agić, MJ Aranzabe, M Asahara, A Atutxa, M Ballesteros, J Bauer, ...
Universal Dependencies Consortium, 2015
1662015
A linguistic evaluation of rule-based, phrase-based, and neural MT engines
A Burchardt, V Macketanz, J Dehdari, G Heigold, JT Peter, P Williams
The Prague Bulletin of Mathematical Linguistics 108 (1), 159-170, 2017
502017
Machine translation: Phrase-based, rule-based and neural approaches with linguistic evaluation
V Macketanz, E Avramidis, A Burchardt, J Helcl, A Srivastava
Cybernetics and Information Technologies 17 (2), 28-43, 2017
152017
Fine-grained evaluation of German-English machine translation based on a test suite
V Macketanz, E Avramidis, A Burchardt, H Uszkoreit
arXiv preprint arXiv:1910.07460, 2019
102019
Deeper machine translation and evaluation for German
E Avramidis, V Macketanz, A Burchardt, J Helcl, H Uszkoreit
Proceedings of the 2nd Deep Machine Translation Workshop, 29-38, 2016
82016
DFKI’s system for WMT16 IT-domain task, including analysis of systematic errors
E Avramidis, A Burchardt, V Macketanz, A Srivastava
Proceedings of the First Conference on Machine Translation: Volume 2, Shared …, 2016
72016
Can out-of-the-box NMT Beat a Domain-trained Moses on Technical Data
A Beyer, V Macketanz, A Burchardt, P Williams
Proceedings of EAMT User Studies and Project/Product Descriptions, 41-46, 2017
52017
Train, sort, explain: Learning to diagnose translation models
R Schwarzenberg, D Harbecke, V Macketanz, E Avramidis, S Möller
arXiv preprint arXiv:1903.12017, 2019
42019
Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically motivated Test Suite
E Avramidis, V Macketanz, A Lommel, H Uszkoreit
Proceedings of the AMTA 2018 Workshop on Translation Quality Estimation and …, 2018
42018
Linguistic evaluation of german-english machine translation using a test suite
E Avramidis, V Macketanz, U Strohriegel, H Uszkoreit
arXiv preprint arXiv:1910.07457, 2019
32019
TQ-AutoTest–An Automated Test Suite for (Machine) Translation Quality
V Macketanz, R Ai, A Burchardt, H Uszkoreit
Proceedings of the Eleventh International Conference on Language Resources …, 2018
12018
Towards Deeper MT: Parallel Treebanks, Entity Linking, and Linguistic Evaluation
A Srivastava, V Macketanz, A Burchardt, E Avramidis
The Workshop on Deep Language Processing for Quality Machine Translation …, 2016
12016
Fine-grained linguistic evaluation for state-of-the-art Machine Translation
E Avramidis, V Macketanz, U Strohriegel, A Burchardt, S Möller
arXiv preprint arXiv:2010.06359, 2020
2020
A new deal for translation quality
A Burchardt, A Lommel, V Macketanz
Universal Access in the Information Society, 1-15, 2020
2020
Fine-grained evaluation of Quality Estimation for Machine translation based on a linguistically-motivated Test Suite
A Eleftherios, V Macketanz, A Lommel, H Uszkoreit
arXiv preprint arXiv:1910.07468, 2019
2019
Evaluating the grammatical performance of German-English Machine Translation using a Test Suite
E Avramidis, V Macketanz, U Strohriegel, H Uszkoreit
TQ-AUTOTEST: NOVEL ANALYTICAL QUALITY MEASURE CONFIRMS THAT DEEPL IS BETTER THAN GOOGLE TRANSLATE
V Macketanz, A Burchardt, H Uszkoreit
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