Bilingual Methods for Adaptive Training Data Selection for Machine Translation

no code implementations • AMTA 2016 • Boxing Chen, Roland Kuhn, George Foster, Colin Cherry, Fei Huang

In this paper, we propose a new data selection method which uses semi-supervised convolutional neural networks based on bitokens (Bi-SSCNNs) for training machine translation systems from a large bilingual corpus.

Machine Translation NMT +2

The Indigenous Languages Technology project at NRC Canada: An empowerment-oriented approach to developing language software

no code implementations • COLING 2020 • Roland Kuhn, Fineen Davis, Alain D{\'e}silets, Eric Joanis, Anna Kazantseva, Rebecca Knowles, Patrick Littell, Delaney Lothian, Aidan Pine, Caroline Running Wolf, Eddie Santos, Darlene Stewart, Gilles Boulianne, Vishwa Gupta, Brian Maracle Owennat{\'e}kha, Akwirat{\'e}kha{'} Martin, Christopher Cox, Marie-Odile Junker, Olivia Sammons, Delasie Torkornoo, Nathan Thanyeht{\'e}nhas Brinklow, Sara Child, Beno{\^\i}t Farley, David Huggins-Daines, Daisy Rosenblum, Heather Souter

This paper surveys the first, three-year phase of a project at the National Research Council of Canada that is developing software to assist Indigenous communities in Canada in preserving their languages and extending their use.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

A Challenge Set for French --> English Machine Translation

no code implementations • 7 Jun 2018 • Pierre Isabelle, Roland Kuhn

We present a challenge set for French --> English machine translation based on the approach introduced in Isabelle, Cherry and Foster (EMNLP 2017).

Machine Translation Translation