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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. - : arXiv, 2021 BASE Show 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 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.475/ Abstract: Recent advances in neural machine translation (NMT) have pushed the quality of machine translation systems to the point where they are becoming widely adopted to build competitive systems. However, there is still a large number of languages that are yet to reap the benefits of NMT. In this paper, we provide the first large-scale case study of the practical application of MT in the Turkic language family in order to realize the gains of NMT for Turkic languages under high-resource to extremely low-resource scenarios. In addition to presenting an extensive analysis that identifies the bottlenecks towards building competitive systems to ameliorate data scarcity, our study has several key contributions, including, i) a large parallel corpus covering 22 Turkic languages consisting of common public datasets in combination with new datasets of approximately 2 million parallel sentences, ii) bilingual baselines for 26 language pairs, iii) ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing URL: https://dx.doi.org/10.48448/512s-v754 https://underline.io/lecture/37958-a-large-scale-study-of-machine-translation-in-turkic-languages BASE Hide 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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