Search Results for author: Rebecca Knowles

Found 25 papers, 2 papers with code

NRC-CNRC Systems for Upper Sorbian-German and Lower Sorbian-German Machine Translation 2021

no code implementations WMT (EMNLP) 2021 Rebecca Knowles, Samuel Larkin

We describe our neural machine translation systems for the 2021 shared task on Unsupervised and Very Low Resource Supervised MT, translating between Upper Sorbian and German (low-resource) and between Lower Sorbian and German (unsupervised).

Machine Translation Transfer Learning +1

On the Stability of System Rankings at WMT

1 code implementation WMT (EMNLP) 2021 Rebecca Knowles

The current approach to collecting human judgments of machine translation quality for the news translation task at WMT – segment rating with document context – is the most recent in a sequence of changes to WMT human annotation protocol.

Machine Translation Translation

NRC Systems for Low Resource German-Upper Sorbian Machine Translation 2020: Transfer Learning with Lexical Modifications

no code implementations WMT (EMNLP) 2020 Rebecca Knowles, Samuel Larkin, Darlene Stewart, Patrick Littell

We describe the National Research Council of Canada (NRC) neural machine translation systems for the German-Upper Sorbian supervised track of the 2020 shared task on Unsupervised MT and Very Low Resource Supervised MT.

Machine Translation Transfer Learning +1

Like Chalk and Cheese? On the Effects of Translationese in MT Training

no code implementations MTSummit 2021 Samuel Larkin, Michel Simard, Rebecca Knowles

We revisit the topic of translation direction in the data used for training neural machine translation systems and focusing on a real-world scenario with known translation direction and imbalances in translation direction: the Canadian Hansard.

Machine Translation Translation

Neural Interactive Translation Prediction

no code implementations AMTA 2016 Rebecca Knowles, Philipp Koehn

We present an interactive translation prediction method based on neural machine translation.

Machine Translation Translation

Translation Memories as Baselines for Low-Resource Machine Translation

no code implementations LREC 2022 Rebecca Knowles, Patrick Littell

Low-resource machine translation research often requires building baselines to benchmark estimates of progress in translation quality.

Machine Translation Translation

NRC Systems for the 2020 Inuktitut-English News Translation Task

no code implementations WMT (EMNLP) 2020 Rebecca Knowles, Darlene Stewart, Samuel Larkin, Patrick Littell

We describe the National Research Council of Canada (NRC) submissions for the 2020 Inuktitut-English shared task on news translation at the Fifth Conference on Machine Translation (WMT20).

Machine Translation Translation

The Nunavut Hansard Inuktitut--English Parallel Corpus 3.0 with Preliminary Machine Translation Results

no code implementations LREC 2020 Eric Joanis, Rebecca Knowles, Rol Kuhn, , Samuel Larkin, Patrick Littell, Chi-kiu Lo, Darlene Stewart, Jeffrey Micher

This paper describes a newly released sentence-aligned Inuktitut{--}English corpus based on the proceedings of the Legislative Assembly of Nunavut, covering sessions from April 1999 to June 2017.

Machine Translation NMT +2

Context and Copying in Neural Machine Translation

no code implementations EMNLP 2018 Rebecca Knowles, Philipp Koehn

In this work, we show that they learn to copy words based on both the context in which the words appear as well as features of the words themselves.

Machine Translation Translation

Document-Level Adaptation for Neural Machine Translation

no code implementations WS 2018 Sachith Sri Ram Kothur, Rebecca Knowles, Philipp Koehn

It is common practice to adapt machine translation systems to novel domains, but even a well-adapted system may be able to perform better on a particular document if it were to learn from a translator{'}s corrections within the document itself.

Machine Translation Sentence +2

Six Challenges for Neural Machine Translation

no code implementations WS 2017 Philipp Koehn, Rebecca Knowles

We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search.

Machine Translation Translation +1

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