most citedAspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CL2020★ 2 cited

Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios

Daniel Torregrosa, Nivranshu Pasricha, Maraim Masoud +4

Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate text from source to target l…

cs.CL2018

Fast Neural Machine Translation Implementation

Hieu Hoang, Tomasz Dwojak, Rihards Krislauks +2

This paper describes the submissions to the efficiency track for GPUs at the Workshop for Neural Machine Translation and Generation by members of the University of Edinburgh, Adam…