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20172023
most citedMultiMWE: Building a Multi-lingual Multi-Word Expression (MWE) Parallel Corpora

6 citations · 30 across the 8 of their papers we have counts for

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Showing 2021 · cs.CLShow all

5 papers · 2 filters

cs.CL2021★ 4 cited

HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation

Serge Gladkoff, Lifeng Han

Traditional automatic evaluation metrics for machine translation have been widely criticized by linguists due to their low accuracy, lack of transparency, focus on language mechani…

cs.CL2021

Measuring Uncertainty in Translation Quality Evaluation (TQE)

Serge Gladkoff, Irina Sorokina, Lifeng Han +1

From both human translators (HT) and machine translation (MT) researchers' point of view, translation quality evaluation (TQE) is an essential task. Translation service providers (…

cs.CL2021

cushLEPOR: customising hLEPOR metric using Optuna for higher agreement with human judgments or pre-trained language model LaBSE

Lifeng Han, Irina Sorokina, Gleb Erofeev +1

Human evaluation has always been expensive while researchers struggle to trust the automatic metrics. To address this, we propose to customise traditional metrics by taking advanta…

cs.CL2021

Translation Quality Assessment: A Brief Survey on Manual and Automatic Methods

Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton

To facilitate effective translation modeling and translation studies, one of the crucial questions to address is how to assess translation quality. From the perspectives of accurac…

cs.CL2021★ 4 cited

Chinese Character Decomposition for Neural MT with Multi-Word Expressions

Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton +1

Chinese character decomposition has been used as a feature to enhance Machine Translation (MT) models, combining radicals into character and word level models. Recent work has inve…