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Simple Search
Hits 1 – 12 of 12
1
Europarl Direct Translationese Dataset ...
Amponsah-Kaakyire, Kwabena
;
Pylypenko, Daria
;
España-Bonet, Cristina
. - : Zenodo, 2021
BASE
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2
Europarl Direct Translationese Dataset ...
Amponsah-Kaakyire, Kwabena
;
Pylypenko, Daria
;
España-Bonet, Cristina
. - : Zenodo, 2021
BASE
Show details
3
Europarl Direct Translationese Dataset ...
Amponsah-Kaakyire, Kwabena
;
Pylypenko, Daria
;
España-Bonet, Cristina
. - : Zenodo, 2021
BASE
Show details
4
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
Ruiter, Dana
;
Klakow, Dietrich
;
van Genabith, Josef
. - : arXiv, 2021
BASE
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5
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
Pylypenko, Daria
;
Amponsah-Kaakyire, Kwabena
;
Chowdhury, Koel Dutta
;
van Genabith, Josef
;
España-Bonet, Cristina
. - : arXiv, 2021
Abstract:
Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural architectures without manual feature engineering have been less explored for this task. In this work, we (i) compare the traditional feature-engineering-based approach to the feature-learning-based one and (ii) analyse the neural architectures in order to investigate how well the hand-crafted features explain the variance in the neural models' predictions. We use pre-trained neural word embeddings, as well as several end-to-end neural architectures in both monolingual and multilingual settings and compare them to feature-engineering-based SVM classifiers. We show that (i) neural architectures outperform other approaches by more than 20 accuracy points, with the BERT-based model performing the best in both the monolingual and multilingual settings; (ii) while many individual hand-crafted translationese features correlate with ... : 9 pages, 5 pages appendix, 2 figures, 7 tables. The first 3 authors contributed equally. Accepted to EMNLP 2021, Main Conference ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/2109.07604
https://dx.doi.org/10.48550/arxiv.2109.07604
BASE
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6
Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation Output ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Herbig, Nico
;
Krueger, Antonio
. - : Underline Science Inc., 2021
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7
Multi-Head Highly Parallelized LSTM Decoder for Neural Machine Translation ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Liu, Qiuhui
;
van Genabith, Josef
. - : Underline Science Inc., 2021
BASE
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8
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Amponsah-Kaakyire, Kwabena
;
Dutta Chowdhury, Koel
. - : Underline Science Inc., 2021
BASE
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9
Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Liu, Qiuhui
;
van Genabith, Josef
. - : Underline Science Inc., 2021
BASE
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10
A Bidirectional Transformer Based Alignment Model for Unsupervised Word Alignment ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
van Genabith, Josef
;
Zhang, Jingyi
. - : Underline Science Inc., 2021
BASE
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11
Automatic classification of human translation and machine translation : a study from the perspective of lexical diversity
Fu, Yingxue
;
Nederhof, Mark Jan
. - : Linkoping University Electronic Press, 2021
BASE
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12
Transformer-based NMT : modeling, training and implementation
Xu, Hongfei
. - : Saarländische Universitäts- und Landesbibliothek, 2021
BASE
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