Results 31 to 40 of about 4,220,052 (297)
Humanities & Social Sciences Communications, 2023 Machine translation has become a popular option for news circulation, due to its speed, cost-effectiveness and improving quality. However, it still remains uncertain whether machine translation is effective in helping novice translators in news ...
Yanxia Yang +3 more
doaj +1 more source
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. BART is trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.
M. Lewis +7 more
semanticscholar +1 more source
A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Non-autoregressive (NAR) generation, which is first proposed in neural machine translation (NMT) to speed up inference, has attracted much attention in both machine learning and natural language processing communities.
Yisheng Xiao +6 more
semanticscholar +1 more source
Creativity in translation: machine translation as a constraint for literary texts [PDF]
Translation Spaces, 2022 This article presents the results of a study involving the translation of a short story by Kurt Vonnegut from English to Catalan and Dutch using three modalities: machine-translation (MT), post-editing (PE) and translation without aid (HT).
Ana Guerberof Arenas, Antonio Toral
semanticscholar +1 more source
Conference on Machine Translation, 2023 This paper presents the results of the General Machine Translation Task organised as part of the 2023 Conference on Machine Translation (WMT). In the general MT task, participants were asked to build machine translation systems for any of 8 language ...
Tom Kocmi +20 more
semanticscholar +1 more source
Neural Machine Translation for Low-resource Languages: A Survey [PDF]
ACM Computing Surveys, 2021 Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since the early 2000s and has already entered a mature phase. While considered the most widely used solution for Machine Translation, its performance on low-resource ...
Surangika Ranathunga +5 more
semanticscholar +1 more source
Sovremennye Issledovaniâ Socialʹnyh Problem, 2022 The article is devoted to the analysis of the psychological scientific text machine translation (from the English language to the Russian one). On the material of the Russian machine translation of an informational brochure, potential difficulties were ...
Ksenia V. Antaeva, Yulia S. Elagina
doaj +1 more source
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Existing multilingual machine translation approaches mainly focus on English-centric directions, while the non-English directions still lag behind. In this work, we aim to build a many-to-many translation system with an emphasis on the quality of non ...
Xiao Pan +3 more
semanticscholar +1 more source
Conference on Machine Translation, 2023 While large language models have made remarkable advancements in natural language generation, their potential in machine translation, especially when fine-tuned, remains under-explored.
Xuan Zhang +3 more
semanticscholar +1 more source
The Curious Case of Hallucinations in Neural Machine Translation [PDF]
North American Chapter of the Association for Computational Linguistics, 2021 In this work, we study hallucinations in Neural Machine Translation (NMT), which lie at an extreme end on the spectrum of NMT pathologies. Firstly, we connect the phenomenon of hallucinations under source perturbation to the Long-Tail theory of Feldman ...
Vikas Raunak +2 more
semanticscholar +1 more source