Results 41 to 50 of about 521,807 (336)
Studia Rossica Posnaniensia, 2019 Machine translation (MT) is a relatively new field of science. MT systems are evolving in certain directions. The article discusses the possibilities and the future of systems currently offered to public by the biggest technological companies focusing on
Jakub Olas
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Lattice Desegmentation for Statistical Machine Translation [PDF]
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2014 Morphological segmentation is an effective sparsity reduction strategy for statistical machine translation (SMT) involving morphologically complex languages. When translating into a segmented language, an extra step is required to desegment the output; previous studies have desegmented the 1-best output from the decoder.
Salameh, Mohammad +2 more
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Advance Research on Neural Machine Translation Integrating Linguistic Knowledge
Jisuanji kexue yu tansuo, 2021 Although neural machine translation has become the mainstream method and paradigm in the current research and application of machine translation, there are also some problems such as the fluent but not faithful of the translation results, difficult ...
GUO Wanghao, FAN Jiangwei, ZHANG Keliang
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Machine Translation, 2019 This paper presents a comparison of post-editing (PE) changes performed on English-to-Finnish neural (NMT), rule-based (RBMT) and statistical machine translation (SMT) output, combining a product-based and a process-based approach.
Maarit Koponen +2 more
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Conference on Machine Translation, 2019 This paper presents the NICT’s participation in the WMT19 unsupervised news translation task. We participated in the unsupervised translation direction: German-Czech.
Benjamin Marie +6 more
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Phrasetable smoothing for statistical machine translation [PDF]
Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing - EMNLP '06, 2006 We discuss different strategies for smoothing the phrasetable in Statistical MT, and give results over a range of translation settings. We show that any type of smoothing is a better idea than the relative-frequency estimates that are often used. The best smoothing techniques yield consistent gains of approximately 1% (absolute) according to the BLEU ...
Foster, George +2 more
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Findings of the 2015 Workshop on Statistical Machine Translation [PDF]
Proceedings of the Tenth Workshop on Statistical Machine Translation, 2015 This paper presents the results of the WMT15 shared tasks, which included a standard news translation task, a metrics task, a tuning task, a task for run-time estimation of machine translation quality, and an automatic post-editing task. This year, 68 machine translation systems from 24 institutions were submitted to the ten translation directions in ...
Bojar, Ond\v{r}ej +13 more
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A Critique of Statistical Machine Translation
Linguistica Antverpiensia, New Series – Themes in Translation Studies, 2021 Phrase-Based Statistical Machine Translation (PB-SMT) is clearly the leading paradigm in the field today. Nevertheless—and this may come as some surprise to the PB-SMT community—most translators and, somewhat more surprisingly perhaps, many experienced MT protagonists find the basic model extremely difficult to understand.
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Combining SMT and NMT back-translated data for efficient NMT [PDF]
, 2019 Neural Machine Translation (NMT) models achieve their best performance when large sets of parallel data are used for training. Consequently, techniques for augmenting the training set have become popular recently. One of these methods is back-translation
Maillette de Buy Wenniger, Gideon +4 more
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Machine Translation in Indian Languages: Challenges and Resolution
Journal of Intelligent Systems, 2019 English to Indian language machine translation poses the challenge of structural and morphological divergence. This paper describes English to Indian language statistical machine translation using preordering and suffix separation.
Patel Raj Nath +2 more
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