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The effect of domain and diacritics in Yorùbá-English neural machine translation
In: 18th Biennial Machine Translation Summit ; https://hal.inria.fr/hal-03350967 ; 18th Biennial Machine Translation Summit, Aug 2021, Orlando, United States (2021)
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Europarl Direct Translationese Dataset ...
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Europarl Direct Translationese Dataset ...
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Europarl Direct Translationese Dataset ...
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A Data Augmentation Approach for Sign-Language-To-Text Translation In-The-Wild ...
Nunnari, Fabrizio; España-Bonet, Cristina; Avramidis, Eleftherios. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation ...
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Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
Abstract: For most language combinations, parallel data is either scarce or simply unavailable. To address this, unsupervised machine translation (UMT) exploits large amounts of monolingual data by using synthetic data generation techniques such as back-translation and noising, while self-supervised NMT (SSNMT) identifies parallel sentences in smaller comparable data and trains on them. To date, the inclusion of UMT data generation techniques in SSNMT has not been investigated. We show that including UMT techniques into SSNMT significantly outperforms SSNMT and UMT on all tested language pairs, with improvements of up to +4.3 BLEU, +50.8 BLEU, +51.5 over SSNMT, statistical UMT and hybrid UMT, respectively, on Afrikaans to English. We further show that the combination of multilingual denoising autoencoding, SSNMT with backtranslation and bilingual finetuning enables us to learn machine translation even for distant language pairs for which only small amounts of monolingual data are available, e.g. yielding BLEU scores ... : 11 pages, 8 figures, accepted at MT-Summit 2021 (Research Track) ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2107.08772
https://arxiv.org/abs/2107.08772
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Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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10
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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11
Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction ...
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WTC1.1 (WikiTailor corpus v. 1.1) ...
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MT models for multilingual CLuBS engine (en-de-fr-es) ...
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WTC1.0 (WikiTailor corpus v. 1.0) ...
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WTC1.1 (WikiTailor corpus v. 1.1) ...
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MT models for multilingual CLuBS engine (en-de-fr-es) ...
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17
Multilingual and Interlingual Semantic Representations for Natural Language Processing: A Brief Introduction
In: Computational Linguistics, Vol 46, Iss 2, Pp 249-255 (2020) (2020)
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GeBioToolkit: Automatic Extraction of Gender-Balanced Multilingual Corpus of Wikipedia Biographies ...
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Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yorùbá and Twi ...
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Query Translation for Cross-lingual Search in the Academic Search Engine PubPsych ...
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