conference-paper
Open access
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies
Research footprint
At a glance
- Citations
- 74
- References
- 70
- Comments
- 0
Paper overview
Öz
Transfer learning or multilingual model is essential for low-resource neural machine translation (NMT), but the applicability is limited to cognate languages by sharing their vocabularies. This paper shows effective techniques to transfer a pre-trained NMT model to a new, unrelated language without shared vocabularies.
Record transparency
Publication details
- DOI
- 10.18653/v1/p19-1120
- OpenAlex
- W2952614664
- Document type
- conference-paper
- Language
- EN
- Last metadata update
Comments
Oturum Açın to join the discussion.