Type

Conference Proceedings

Authors

Qun Liu
Andy Way
Peyman Passban

Subjects

Linguistics

Topics
machine translating neural machine translation russian morphologically complex word turkish farsi german morphologically rich languages

Tailoring neural architectures for translating from morphologically rich languages (2018)

Abstract A morphologically complex word (MCW) is a hierarchical constituent with meaning-preserving subunits, so word-based models which rely on surface forms might not be powerful enough to translate such structures. When translating from morphologically rich languages (MRLs), a source word could be mapped to several words or even a full sentence on the target side, which means an MCW should not be treated as an atomic unit. In order to provide better translations for MRLs, we boost the existing neural machine translation (NMT) architecture with a doublechannel encoder and a double-attentive decoder. The main goal targeted in this research is to provide richer information on the encoder side and redesign the decoder accordingly to benefit from such information. Our experimental results demonstrate that we could achieve our goal as the proposed model outperforms existing subword- and character-based architectures and showed significant improvements on translating from German, Russian, and Turkish into English.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Qun Liu, Andy Way, Peyman Passban

Experts in our system

1
Qun Liu
Dublin City University
Total Publications: 31
 
2
Andy Way
Dublin City University
Total Publications: 229
 
3
Peyman Passban
Dublin City University
Total Publications: 9