Results 51 to 60 of about 53,972 (305)
Neural machine translation of literary texts from English to Slovene
, 2019 Neural Machine Translation has shown promising performance in literary texts. Since literary machine translation has not yet been researched for the English-toSlovene translation direction, this paper aims to fulfill this gap by presenting a comparison ...
Kuzman, Taja +2 more
core +1 more source
Zero-Shot Neural Machine Translation with Self-Learning Cycle [PDF]
, 2021 Neural Machine Translation (NMT) approaches employing monolingual data are showing steady improvements in resource-rich conditions. However, evaluations using real-world lowresource languages still result in unsatisfactory performance. This work proposes
Marco Turchi +2 more
core
Unsupervised Neural Machine Translation
CoRR, 2017 In spite of the recent success of neural machine translation (NMT) in standard benchmarks, the lack of large parallel corpora poses a major practical problem for many language pairs. There have been several proposals to alleviate this issue with, for instance, triangulation and semi-supervised learning techniques, but they still require a strong cross ...
Mikel Artetxe +3 more
openaire +4 more sources
DESIGN OF TRANSLATION AMBIGUITY ELIMINATION METHOD BASED ON RECURRENT NEURAL NETWORKS [PDF]
Acta Informatica MalaysiaThe ambiguity of language inevitably leads to the ambiguity of translation, and how to deal with translation ambiguity has become a persistent focus of attention for both human translation and machine translation.
Jianzhou Cui
doaj +1 more source
Progress in Machine Translation
Engineering, 2022 After more than 70 years of evolution, great achievements have been made in machine translation. Especially in recent years, translation quality has been greatly improved with the emergence of neural machine translation (NMT).
Haifeng Wang +4 more
doaj +1 more source
A product and process analysis of post-editor corrections on neural, statistical and rule-based machine translation output [PDF]
, 2022 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
core +1 more source
Neural Machine Translation: A Review
Journal of Artificial Intelligence Research, 2020 The field of machine translation (MT), the automatic translation of written text from one natural language into another, has experienced a major paradigm shift in recent years. Statistical MT, which mainly relies on various count-based models and which used to dominate MT research for decades, has largely been superseded by neural machine translation ...
openaire +3 more sources
Neural Machine Translation with Reconstruction
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 Although end-to-end Neural Machine Translation (NMT) has achieved remarkable progress in the past two years, it suffers from a major drawback: translations generated by NMT systems often lack of adequacy. It has been widely observed that NMT tends to repeatedly translate some source words while mistakenly ignoring other words.
Zhaopeng Tu +4 more
openaire +2 more sources
Post-editing neural machine translation versus translation memory segments [PDF]
, 2019 The use of neural machine translation (NMT) in a professional scenario implies a number of challenges despite growing evidence that, in language combinations such as English to Spanish, NMT output quality has already outperformed statistical machine ...
Moorkens, Joss +2 more
core +1 more source
Cost weighting for neural machine translation domain adaptation
, 2017 In this paper, we propose a new domain adaptation technique for neural machine translation called cost weighting, which is appropriate for adaptation scenarios in which a small in-domain data set and a large general-domain data set are available.
Cherry, Colin +7 more
core +1 more source