Results 71 to 80 of about 491,933 (328)
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.
Reheman, Abudurexiti +5 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
Simple, Scalable Adaptation for Neural Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Fine-tuning pre-trained Neural Machine Translation (NMT) models is the dominant approach for adapting to new languages and domains. However, fine-tuning requires adapting and maintaining a separate model for each target task.
Ankur Bapna, N. Arivazhagan, Orhan Firat
semanticscholar +1 more source
Chinese–Spanish neural machine translation enhanced with character and word bitmap fonts [PDF]
, 2017 Recently, machine translation systems based on neural networks have reached state-of-the-art results for some pairs of languages (e.g., German–English). In this paper, we are investigating the performance of neural machine translation in Chinese–Spanish,
A Lavie +6 more
core +2 more sources
Phrase-Based & Neural Unsupervised Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2018 Machine translation systems achieve near human-level performance on some languages, yet their effectiveness strongly relies on the availability of large amounts of parallel sentences, which hinders their applicability to the majority of language pairs ...
Guillaume Lample +4 more
semanticscholar +1 more source
The Helsinki Neural Machine Translation System [PDF]
Proceedings of the Second Conference on Machine Translation, 2017 Proceedings of the Second Conference on Machine Translation (WMT 2017) at EMNLP 2017, Copenhagen ...
Östling, Robert +4 more
openaire +5 more sources
Syntactically Guided Neural Machine Translation [PDF]
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2016 ACL ...
Stahlberg, F +3 more
openaire +3 more sources
Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism [PDF]
North American Chapter of the Association for Computational Linguistics, 2016 We propose multi-way, multilingual neural machine translation. The proposed approach enables a single neural translation model to translate between multiple languages, with a number of parameters that grows only linearly with the number of languages ...
Orhan Firat +2 more
semanticscholar +1 more source
Reduction of Neural Machine Translation Failures by Incorporating Statistical Machine Translation
Mathematics, 2023 This paper proposes a hybrid machine translation (HMT) system that improves the quality of neural machine translation (NMT) by incorporating statistical machine translation (SMT).
Jani Dugonik +3 more
doaj +1 more source
Neural machine translation model combining dependency syntax and LSTM [PDF]
ITM Web of Conferences, 2022 For the problem of the lack of linguistic knowledge in the neural machine translation model, which is called Transformer, and the insufficient flexibility of positional encoding, this paper introduces the dependency syntax analysis and the long short ...
Zheng Xin +3 more
doaj +1 more source