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  1. Recent work on multilingual neural machine translation reported competitive performance with respect to bilingual models and surprisingly good performance even on (zeroshot) translation directions not observed at training time. We investigate here a zero-shot translation in a particularly lowresource multilingual setting. We propose a simple iterative training procedure that leverages a ...
    Author:Surafel M. Lakew, Quintino F. Lotito, Matteo Negri, Marco Turchi, Marcello FedericoPublished:2018
  2. aclanthology.org

    %0 Conference Proceedings %T Improving Zero-Shot Translation of Low-Resource Languages %A Lakew, Surafel M. %A Lotito, Quintino F. %A Negri, Matteo %A Turchi, Marco %A Federico, Marcello %Y Sakti, Sakriani %Y Utiyama, Masao %S Proceedings of the 14th International Conference on Spoken Language Translation %D 2017 %8 dec 14 15 %I International Workshop on Spoken Language Translation %C Tokyo ...
  3. aclanthology.org

    provement in the non-zero-shot language directions. 1. Introduction Machine translation of low-resource languages represents a challenge for neural machine translation (NMT) [1]. Recent efforts in multilingual NMT (Multi-NMT) [2, 3] have shown to improve translation performance in low-resource settings.
  4. surafelml.github.io

    Improving Zero-Shot Translation of Low-Resource Languages S. M. Lakew, Q. F. Lotito, M. Turchi, M. Negri, ... Our approach shows to be effective in improving the two zero-shot directions of our multilingual model. In particular, we observed gains of about 9 BLEU points over a baseline multilingual model and up to 2.08 BLEU over a pivoting ...
  5. researchgate.net

    Using MNMT models can reduce the cost of model training and deployment [6], encourage knowledge transfer between language pairs to improve low-resource translation [11][12][13][14] and even show ...
  6. journals.openedition.org

    Lakew et al. Multilingual NMT for Low Resource Languages r A self-learning approach to improve the zero-shot translation task of a multilingual model. The paper is organized as follows. In Section 2, we present previous works on multilingual NMT, zero-shot NMT, and NMT training with self-generated data. In
  7. semanticscholar.org

    This work proposes a simple iterative training procedure that leverages a duality of translations directly generated by the system for the zero-shot directions, and shows to be effective in improving the two zero- shot directions of the multilingual model. Recent work on multilingual neural machine translation reported competitive performance with respect to bilingual models and surprisingly ...
  8. Although the multilingual Neural Machine Translation(NMT), which extends Google's multilingual NMT, has ability to perform zero-shot translation and the iterative self-learning algorithm can improve the quality of zero-shot translation, it confronts with two problems: the multilingual NMT model is prone to generate wrong target language when implementing zero-shot translation; the self ...
  9. Improving Zero-shot Translation of Low-resource Languages [IWSLT 2017] - surafelml/improving-zeroshot-nmt. ... {Improving zero-shot translation of low-resource languages}, author = {Lakew, Surafel M and Lotito, Quintino F and Negri, Matteo and Turchi, Marco and Federico, ...

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