Existing Sequence-to-Sequence (Seq2Seq) Neural Machine Translation (NMT) shows strong capability with High-Resource Languages (HRLs). However, this approach poses serious challenges when processing Low-Resource Languages (LRLs), because the model expression is limited by the training scale of parallel sentence pairs. This study utilizes adversary and transfer learning techniques to mitigate the lack of sentence pairs in LRL corpora. We propose a new Low resource, Adversarial, Cross-lingual (LAC) model for NMT. In terms of the adversary technique, LAC model consists of a generator and discriminator. The generator is a Seq2Seq model that produces the translations from source to target languages, while the discriminator measures the gap betwee...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Unsupervised cross-lingual pretraining has achieved strong results in neural machine translation (NM...
Cross-lingual natural language inference is a fundamental task in cross-lingual natural language und...
With the advent of deep neural networks in recent years, Neural Machine Translation (NMT) systems ha...
Title: Exploring Benefits of Transfer Learning in Neural Machine Translation Author: Tom Kocmi Depar...
Neural machine translation (NMT) for low-resource languages has drawn great attention in recent year...
Multilingual Neural Machine Translation (MNMT) for low- resource languages (LRL) can be enhanced by ...
Multilingual neural machine translation (M-NMT) has recently shown to improve performance of machine...
Neural machine translation (NMT) has been a mainstream method for the machine translation (MT) task....
2019-02-14We provide new tools and techniques for improving machine translation for low-resource lan...
With economic globalization and the rapid development of the Internet, the connections between diffe...
| openaire: EC/H2020/780069/EU//MeMADThere are several approaches for improving neural machine trans...
Humans benefit from communication but suffer from language barriers. Machine translation (MT) aims t...
Although Neural Machine Translation (NMT) models have advanced state-of-the-art performance in machi...
© Springer International Publishing AG, part of Springer Nature 2018. Neural machine translation (NM...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Unsupervised cross-lingual pretraining has achieved strong results in neural machine translation (NM...
Cross-lingual natural language inference is a fundamental task in cross-lingual natural language und...
With the advent of deep neural networks in recent years, Neural Machine Translation (NMT) systems ha...
Title: Exploring Benefits of Transfer Learning in Neural Machine Translation Author: Tom Kocmi Depar...
Neural machine translation (NMT) for low-resource languages has drawn great attention in recent year...
Multilingual Neural Machine Translation (MNMT) for low- resource languages (LRL) can be enhanced by ...
Multilingual neural machine translation (M-NMT) has recently shown to improve performance of machine...
Neural machine translation (NMT) has been a mainstream method for the machine translation (MT) task....
2019-02-14We provide new tools and techniques for improving machine translation for low-resource lan...
With economic globalization and the rapid development of the Internet, the connections between diffe...
| openaire: EC/H2020/780069/EU//MeMADThere are several approaches for improving neural machine trans...
Humans benefit from communication but suffer from language barriers. Machine translation (MT) aims t...
Although Neural Machine Translation (NMT) models have advanced state-of-the-art performance in machi...
© Springer International Publishing AG, part of Springer Nature 2018. Neural machine translation (NM...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Unsupervised cross-lingual pretraining has achieved strong results in neural machine translation (NM...
Cross-lingual natural language inference is a fundamental task in cross-lingual natural language und...