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Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
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Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation Output ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.799/ Abstract: Compared to fully manual translation, post-editing (PE) machine translation (MT) output can save time and reduce errors. Automatic word-level quality estimation (QE) aims to predict the correctness of words in MT output and holds great promise to aid PE by flagging problematic output. Quality of QE is crucial, as incorrect QE might lead to translators missing errors or wasting time on already correct MT output. Achieving accurate automatic word-level QE is very hard, and it is currently not known (i) at what quality threshold QE is actually beginning to be useful for human PE, and (ii), how to best present word-level QE information to translators. In particular, should word-level QE visualization indicate uncertainty of the QE model or not? In this paper, we address both research questions with real and simulated word-level QE, visualizations, and user studies, where time, subjective ratings, and quality of the final translations ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
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URL: https://underline.io/lecture/37261-investigating-the-helpfulness-of-word-level-quality-estimation-for-post-editing-machine-translation-output https://dx.doi.org/10.48448/jz60-cb48
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Multi-Head Highly Parallelized LSTM Decoder for Neural Machine Translation ...
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Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation ...
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A Bidirectional Transformer Based Alignment Model for Unsupervised Word Alignment ...
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Automatic classification of human translation and machine translation : a study from the perspective of lexical diversity
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Transformer-based NMT : modeling, training and implementation
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Xu, Hongfei. - : Saarländische Universitäts- und Landesbibliothek, 2021
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
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In: Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02892154 ; Language Resources and Evaluation Conference, ELDA/ELRA, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/en/ (2020)
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
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Linguistically inspired morphological inflection with a sequence to sequence model ...
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Probing Word Translations in the Transformer and Trading Decoder for Encoder Layers ...
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Language service provision in the 21st century: challenges, opportunities and educational perspectives for translation studies
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In: ISBN: 9788869234934 ; Bologna Process beyond 2020: Fundamental values of the EHEA pp. 297-303 (2020)
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Deep interactive text prediction and quality estimation in translation interfaces
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In: Hokamp, Christopher M. (2018) Deep interactive text prediction and quality estimation in translation interfaces. PhD thesis, Dublin City University. (2018)
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