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1
Europarl Direct Translationese Dataset ...
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Europarl Direct Translationese Dataset ...
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3
Europarl Direct Translationese Dataset ...
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4
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
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5
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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6
Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation Output ...
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7
Multi-Head Highly Parallelized LSTM Decoder for Neural Machine Translation ...
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8
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.676/ 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) ...
Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
URL: https://underline.io/lecture/38089-comparing-feature-engineering-and-feature-learning-approaches-for-multilingual-translationese-classification
https://dx.doi.org/10.48448/fj59-8z46
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9
Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation ...
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10
A Bidirectional Transformer Based Alignment Model for Unsupervised Word Alignment ...
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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
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12
Transformer-based NMT : modeling, training and implementation
Xu, Hongfei. - : Saarländische Universitäts- und Landesbibliothek, 2021
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