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Boosting Neural Machine Translation with Similar Translations
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In: Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02956324 ; Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle, United States. pp.1570-1579, ⟨10.18653/v1/2020.acl-main.143⟩ (2020)
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Que valent les traducteurs automatiques de la science-fiction ?
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In: ISSN: 2261-6446 ; EISSN: 2261-6470 ; CNRS Le journal ; https://hal.archives-ouvertes.fr/hal-02934841 ; CNRS Le journal, CNRS, 2020 ; https://lejournal.cnrs.fr/billets/que-valent-les-traducteurs-automatiques-de-la-science-fiction (2020)
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Machine Translation for the Normalisation of 17th c. French ; Traduction automatique pour la normalisation du français du XVII e siècle
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In: TALN 2020 ; https://hal.archives-ouvertes.fr/hal-02596669 ; TALN 2020, ATALA, Jun 2020, Nancy, France (2020)
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Czech image captioning, machine translation, sentiment analysis and summarization (Neural Monkey models)
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Parallel text dataset for Neural Machine Translation (French -> Fongbe, French -> Ewe) ...
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Parallel text dataset for Neural Machine Translation (French -> Fongbe, French -> Ewe) ...
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MultiWord Expression Aware Neural Machine Translation ...
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Abstract:
Multiword Expressions (MWEs) are a frequently occurring phenomenon found in all natural languages that is of great importance to linguistic theory, natural language processing applications, and machine translation systems. Neural Machine Translation (NMT) architectures do not handle these expression well and previous studies have not explicitly addressed MWEs in this framework. In this work, we show that using external linguistic resources and data augmentation we can improve both translations of MWEs that occur in the source, and the generation of MWEs on the target, and improve performance by up to 5.09 BLEU points on MWE test sets. We also devise a MWE score to specifically assess the quality of MWE translation which agrees with human evaluation. We make available the MWEscore implementation – along with MWE-annotated training sets and corpus-based lists of MWEs – for reproduction and extension. ...
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Keyword:
multiword expressions, neural machine translation, evaluation
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URL: https://dx.doi.org/10.5281/zenodo.3923508 https://zenodo.org/record/3923508
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The impact of distributed neural machine translation in sentiment analysis ...
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UPC: An Open Word-Sense Annotated Parallel Corpora for Machine Translation Study
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In: Applied Sciences ; Volume 10 ; Issue 11 (2020)
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An English-Chinese Machine Translation and Evaluation Method for Geographical Names
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In: ISPRS International Journal of Geo-Information ; Volume 9 ; Issue 3 (2020)
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Multi-Source Neural Model for Machine Translation of Agglutinative Language
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In: Future Internet ; Volume 12 ; Issue 6 (2020)
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Hybrid Translation with Classification: Revisiting Rule-Based and Neural Machine Translation
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In: Electronics ; Volume 9 ; Issue 2 (2020)
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Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
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Groundbreaking technologies in machine translation ; Революционные технологии в области машинного перевода
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Bridging the “gApp”: improving neural machine translation systems for multiword expression detection
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In: 11 ; 1 ; 61 ; 80 (2020)
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Human-assisted Neural Machine Translation: Harnessing Human Feedback for Machine Translation
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Open source quality control tool for translation memory using artificial intelligence
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