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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)
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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)
Abstract: From both human translators (HT) and machine translation (MT) researchers' point of view, translation quality evaluation (TQE) is an essential task. This is especially the case, when language service providers (LSPs) face huge amount of request frequently from their clients and users to acquire high-quality translations. While automatic translation quality assessment (TQA) metrics and quality estimation (QE) tools are widely available and easy to access, human assessment from professional translators (HAP) are often chosen as the golden standard \cite{han-etal-2021-TQA}. One challenge that comes to this point is this: \textit{to avoid the overall text quality checking from both cost and efficiency perspectives, how to choose the confidence sample size of the translated text, so as to properly estimate the overall text or document translation quality}? This work carries out such an motivated research to correctly estimate the confidence intervals \cite{Brown_etal2001Interval} regarding the sample size of translated text, e.g. the amount of words or sentences, that needs to be taken into account for confident evaluation of overall translation quality. The methodology we applied for this work is from Bernoulli Statistical Distribution Modelling (BSDM) and Monte Carlo Sampling Analysis (MCSA).
Keyword: Algorithms; Artificial intelligence; Computational linguistics; Computer software; Information technology; Post-editing Distance; Confidence Intervals; Monte Carlo Modeling; Bernoulli Statistics; Probabilities; Quality Estimation; Statistics; Stochastic analysis; Translation Quality Evaluation
URL: http://doras.dcu.ie/26281/
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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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