Results 51 to 60 of about 47,700 (259)

Prompting Neural Machine Translation with Translation Memories

Proceedings of the AAAI Conference on Artificial Intelligence, 2023
Improving machine translation (MT) systems with translation memories (TMs) is of great interest to practitioners in the MT community. However, previous approaches require either a significant update of the model architecture and/or additional training efforts to make the models well-behaved when TMs are taken as additional input.
Abudurexiti Reheman, Tao Zhou, Yingfeng Luo, Di Yang, Tong Xiao 0001, Jingbo Zhu   +5 more
openaire   +2 more sources

Boosting Neural Machine Translation

CoRR, 2016
published in IJCNLP ...
Dakun Zhang, Jungi Kim, Josep Maria Crego, Jean Senellart   +3 more
openaire   +3 more sources

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, Shafiq R. Joty, Lluís Màrquez, Preslav Nakov   +3 more
openaire   +2 more sources

Lexical Diversity in Statistical and Neural Machine Translation

Information, 2022
Neural machine translation systems have revolutionized translation processes in terms of quantity and speed in recent years, and they have even been claimed to achieve human parity.
Mojca Brglez, Špela Vintar
doaj   +1 more source

Iterative Back-Translation for Neural Machine Translation [PDF]

Proceedings of the 2nd Workshop on Neural Machine Translation and Generation, 2018
We present iterative back-translation, a method for generating increasingly better synthetic parallel data from monolingual data to train neural machine translation systems. Our proposed method is very simple yet effective and highly applicable in practice. We demonstrate improvements in neural machine translation quality in both high and low resourced
Hoang, Cong Duy Vu, Koehn, Philipp, Haffari, Gholamreza, Cohn, Trevor   +3 more
openaire   +2 more sources

Generalizing Back-Translation in Neural Machine Translation [PDF]

Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers), 2019
Published by Association for Computational Linguistics (ACL), Stroudsburg ...
Graça, Miguel M., Kim, Yunsu, Schamper, Julian, Khadivi, Shahram, Ney, Hermann   +4 more
openaire   +3 more sources

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, Gorka Labaka, Eneko Agirre, Kyunghyun Cho   +3 more
openaire   +4 more sources

DESIGN OF TRANSLATION AMBIGUITY ELIMINATION METHOD BASED ON RECURRENT NEURAL NETWORKS [PDF]

Acta Informatica Malaysia
The 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, Hua Wu, Zhongjun He, Liang Huang, Kenneth Ward Church   +4 more
doaj   +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