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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets Caswell, Isaac; Kreutzer, Julia; Wang, Lisa... In: https://hal.inria.fr/hal-03177623 ; 2021 (2021) BASE Show details 2 A Large-Scale Study of Machine Translation in the Turkic Languages ... Mirzakhalov, Jamshidbek; Babu, Anoop; Ataman, Duygu. - : arXiv, 2021 BASE Show details 3 Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets ... Kreutzer, Julia; Caswell, Isaac; Wang, Lisa. - : arXiv, 2021 BASE Show details 4 Evaluating Multiway Multilingual NMT in the Turkic Languages ... Mirzakhalov, Jamshidbek; Babu, Anoop; Kunafin, Aigiz; Wahab, Ahsan; Moydinboyev, Behzod; Ivanova, Sardana; Uzokova, Mokhiyakhon; Pulatova, Shaxnoza; Ataman, Duygu; Kreutzer, Julia; Tyers, Francis; Firat, Orhan; Licato, John; Chellappan, Sriram. - : arXiv, 2021 Abstract: Despite the increasing number of large and comprehensive machine translation (MT) systems, evaluation of these methods in various languages has been restrained by the lack of high-quality parallel corpora as well as engagement with the people that speak these languages. In this study, we present an evaluation of state-of-the-art approaches to training and evaluating MT systems in 22 languages from the Turkic language family, most of which being extremely under-explored. First, we adopt the TIL Corpus with a few key improvements to the training and the evaluation sets. Then, we train 26 bilingual baselines as well as a multi-way neural MT (MNMT) model using the corpus and perform an extensive analysis using automatic metrics as well as human evaluations. We find that the MNMT model outperforms almost all bilingual baselines in the out-of-domain test sets and finetuning the model on a downstream task of a single pair also results in a huge performance boost in both low- and high-resource scenarios. Our ... : 9 pages, 3 figures, 7 tables. To be presented at WMT 2021 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2109.06262 https://arxiv.org/abs/2109.06262 BASE Hide details 5 A Large-Scale Study of Machine Translation in Turkic Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Mirzakhalov, Jamshidbek. - : Underline Science Inc., 2021 BASE Show details 6 Can Transformer Language Models Predict Psychometric Properties? ... Laverghetta, Antonio; Nighojkar, Animesh; Mirzakhalov, Jamshidbek. - : arXiv, 2021 BASE Show details 7 Evaluating Multiway Multilingual NMT in the Turkic Languages ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Mirzakhalov, Jamshidbek. - : Underline Science Inc., 2021 BASE Show details 8 Can Transformer Langauge Models Predict Psychometric Properties? ... 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; Laverghetta Jr., Antonio; Licato, John. - : Underline Science Inc., 2021 BASE Show details 9 Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages Mirzakhalov, Jamshidbek. - : Digital Commons @ University of South Florida, 2021 In: Graduate Theses and Dissertations (2021) BASE Show details

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