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1
Towards an empirical evaluation of translated texts and translation quality ; Vers une évaluation empirique des textes traduits et de la qualité en traduction
In: https://hal.archives-ouvertes.fr/hal-03584752 ; 2022 (2022)
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2
Neural MT and Human Post-editing : a Method to Improve Editorial Quality
In: ISSN: 1134-8941 ; Interlingüística ; https://halshs.archives-ouvertes.fr/halshs-03603590 ; Interlingüística, Alacant [Spain] : Universitat Autònoma de Barcelona, 2022, pp.15-36 (2022)
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3
Translation and Cultural Adaptation into Portuguese of the Quality of Dying and Death Scale for Family Members of Patients in Intensive Care Units
In: International Journal of Environmental Research and Public Health; Volume 19; Issue 6; Pages: 3614 (2022)
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4
Neural Models for Measuring Confidence on Interactive Machine Translation Systems
In: Applied Sciences; Volume 12; Issue 3; Pages: 1100 (2022)
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5
Translate Wisely! An Evaluation of Close and Adaptive Translation Procedures in an Experiment Involving Questionnaire Translation
In: International journal of sociology ; 51 ; 2 ; 135-162 (2022)
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6
Pushing the right buttons: adversarial evaluation of quality estimation
In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022)
Abstract: © (2021) The Authors. Published by Association for Computational Linguistics. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://aclanthology.org/2021.wmt-1.67 ; Current Machine Translation (MT) systems achieve very good results on a growing variety of language pairs and datasets. However, they are known to produce fluent translation outputs that can contain important meaning errors, thus undermining their reliability in practice. Quality Estimation (QE) is the task of automatically assessing the performance of MT systems at test time. Thus, in order to be useful, QE systems should be able to detect such errors. However, this ability is yet to be tested in the current evaluation practices, where QE systems are assessed only in terms of their correlation with human judgements. In this work, we bridge this gap by proposing a general methodology for adversarial testing of QE for MT. First, we show that despite a high correlation with human judgements achieved by the recent SOTA, certain types of meaning errors are still problematic for QE to detect. Second, we show that on average, the ability of a given model to discriminate between meaningpreserving and meaning-altering perturbations is predictive of its overall performance, thus potentially allowing for comparing QE systems without relying on manual quality annotation.
Keyword: adversarial evaluation; machine translation; quality estimation
URL: http://hdl.handle.net/2436/624376
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7
Translation quality assessment: a brief survey on manual and automatic methods
In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2021) Translation quality assessment: a brief survey on manual and automatic methods. In: MoTra21: Workshop on Modelling Translation: Translatology in the Digital Age, 31 May- 2 Jun 2021, Rejkjavik, Iceland (Online). (In Press) (2021)
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8
Monte Carlo modelling of confidence intervals in translation quality evaluation (TQE) and post-editing dstance (PED) measurement
In: Alekseeva, Alexandra orcid:0000-0002-7990-4592 , Gladkoff, Serge, Sorokina, Irina and Han, Lifeng orcid:0000-0002-3221-2185 (2021) Monte Carlo modelling of confidence intervals in translation quality evaluation (TQE) and post-editing dstance (PED) measurement. In: Metrics 2021: Workshop on Informetric and Scientometric Research (SIG-MET), 23-24 Oct 2021, Online. (2021)
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9
Uncovering Machine Translationese Using Corpus Analysis Techniques to Distinguish between Original and Machine­-Translated French
In: ISSN: 1027-8559 ; Translation Quarterly ; https://hal.archives-ouvertes.fr/hal-03406287 ; Translation Quarterly, The Hong Kong Translation Society, 2021, pp.21-45 (2021)
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10
Towards Sustainable Use of Machine Translation: Usability and Perceived Quality from the End-User Perspective
In: Sustainability; Volume 13; Issue 23; Pages: 13430 (2021)
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11
The Role of Machine Translation Quality Estimation in the Post-Editing Workflow
In: Informatics ; Volume 8 ; Issue 3 (2021)
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12
Afterword: Future Directions in Multinational, Multiregional, and Multicultural (3MC) Survey Research
In: The essential role of language in survey research ; 243-256 (2021)
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13
Human evaluation of three machine translation systems : from quality to attitudes by professional translators
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14
Assessing the use of back translation: the shortcomings of back translation as a quality testing method
In: International Journal of Social Research Methodology ; 20 ; 6 ; 573-584 (2021)
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15
Effects of Time Pressure on Translation: A Psycho-physiological, Behavioural-cognitive and Performance-based Study
WENG, YU. - 2021
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16
Machine translation systems and quality assessment: a systematic review
Rivera Trigueros, Irene. - : Springer, 2021
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17
Findings of the WMT 2021 shared task on quality estimation
In: 689 ; 730 (2021)
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18
deepQuest-py: large and distilled models for quality estimation
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations ; 382 ; 389 (2021)
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19
Knowledge distillation for quality estimation
In: 5091 ; 5099 (2021)
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20
Produção de conteúdo bilingue na arqueologia e museologia ; Bilingual approaches in archaeology and museology
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