This review paper discusses how context has been used in neural machine translation
(NMT) in the past two years (2017-2018). Starting with a brief retrospect on the rapid …

An abstract must not change the meaning of the original text. A single most effective way to
achieve that is to increase the amount of copying while still allowing for text abstraction …

Previous studies have shown that initializing neural machine translation (NMT) models with
the pre-trained language models (LM) can speed up the model training and boost the model …

Abstractive summarization generates a concise summary to capture the key ideas of the
source text. This task underpins important applications like information retrieval, document …

Abstract 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 …

We have explored the effect of in domain knowledge during parallel sentence filtering from
in domain corpora. Models built with sentences mined from in domain corpora without …

We present 27 problems encountered in automating the translation of movie/TV show
subtitles. We categorize each problem in one of the three categories viz. problems directly …

La traduction automatique (TA) neuronale a conduit à une amélioration perceptible de la
qualité de traduction et de l'utilisabilité des textes ainsi produits dans un nombre varié de …

As a commercial provider of machine translation, we are constantly training engines for a
variety of uses, languages, and content types. In each case, there can be many variables …

One of the desirable features of a text summarization system is its ability to generalize on
unseen text. In this paper, models representing three main categories viz, Pointer-Generator …