activity
20182021
most citedMultilingual Neural Machine Translation With Soft Decoupled Encoding

43 citations · 43 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2021

It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data

Jinming Zhao, Philip Arthur, Gholamreza Haffari +2

Most existing simultaneous machine translation (SiMT) systems are trained and evaluated on offline translation corpora. We argue that SiMT systems should be trained and tested on r…

cs.CL2020

Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning

Philip Arthur, Trevor Cohn, Gholamreza Haffari

We present a novel approach to efficiently learn a simultaneous translation model with coupled programmer-interpreter policies. First, wepresent an algorithmic oracle to produce or…

cs.CL201943 cited

Multilingual Neural Machine Translation With Soft Decoupled Encoding

Xinyi Wang, Hieu Pham, Philip Arthur +1

Multilingual training of neural machine translation (NMT) systems has led to impressive accuracy improvements on low-resource languages. However, there are still significant challe…

cs.CL2018

XNMT: The eXtensible Neural Machine Translation Toolkit

Graham Neubig, Matthias Sperber, Xinyi Wang +10

This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, w…

cs.CL2018

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop

Odette Scharenborg, Laurent Besacier, Alan Black +16

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and word…