Results 11 to 20 of about 70,068 (263)
A Survey on Hybrid Machine Translation [PDF]
E3S Web of Conferences, 2020 Machine translation has gradually developed in past 1940’s.It has gained more and more attention because of effective and efficient nature. As it makes the translation automatically without the involvement of human efforts. The distinct models of machine
Anugu Anusha, Ramesh Gajula
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Dataset for comparable evaluation of machine translation between 11 South African languages
Data in Brief, 2020 This data article describes the Autshumato machine translation evaluation set. The evaluation set contains data that can be used to evaluate machine translation systems between any of the 11 official South African languages.
Cindy A. McKellar, Martin J. Puttkammer
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Machine translation evaluation with neural networks [PDF]
Computer Speech & Language, 2017 We present a framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a pair of hypotheses, given the reference translation. In this framework, lexical, syntactic and semantic information from the reference and the two hypotheses is embedded into compact ...
Francisco Guzmán +3 more
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Case Study of Improving English-Arabic Translation Using the Transformer Model. [PDF]
International Journal of Intelligent Computing and Information Sciences, 2023 Arabic is a language with rich morphology and few resources. Arabic is therefore recognized as one of the most challenging languages for machine translation.
Donia Gamal +3 more
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Extrinsic Evaluation of Machine Translation Metrics
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023 Automatic machine translation (MT) metrics are widely used to distinguish the translation qualities of machine translation systems across relatively large test sets (system-level evaluation). However, it is unclear if automatic metrics are reliable at distinguishing good translations from bad translations at the sentence level (segment-level evaluation)
Moghe, Nikita +3 more
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Uncertainty-Aware Machine Translation Evaluation [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2021, 2021 Several neural-based metrics have been recently proposed to evaluate machine translation quality. However, all of them resort to point estimates, which provide limited information at segment level. This is made worse as they are trained on noisy, biased and scarce human judgements, often resulting in unreliable quality predictions.
Taisiya Glushkova +3 more
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İstanbul Üniversitesi Çeviribilim Dergisi, 2022 Corpus-based machine translation (MT) has been the main approach to developing and implementing MT systems in both academia and the industry over the last three decades.
Gökhan Doğru
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On the Evaluation of Machine Translation for Terminology Consistency
CoRR, 2021 As neural machine translation (NMT) systems become an important part of professional translator pipelines, a growing body of work focuses on combining NMT with terminologies. In many scenarios and particularly in cases of domain adaptation, one expects the MT output to adhere to the constraints provided by a terminology.
Md Mahfuz Ibn Alam +6 more
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Machine Translation System for the Industry Domain and Croatian Language
Journal of Information and Organizational Sciences, 2020 Machine translation is increasingly becoming a hot research topic in information and communication sciences, computer science and computational linguistics, due to the fact that it enables communication and transferring of meaning across different ...
Ivan Dunđer
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An Overview on Machine Translation Evaluation
CoRR, 2022 Since the 1950s, machine translation (MT) has become one of the important tasks of AI and development, and has experienced several different periods and stages of development, including rule-based methods, statistical methods, and recently proposed neural network-based learning methods.
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