Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

We present a survey on multilingual neural machine translation (MNMT), which has gained
a lot of traction in recent years. MNMT has been useful in improving translation quality as a …

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

A current problem in NLP is massaging and processing low-resource languages which lack
useful training attributes such as supervised data, number of native speakers or experts, etc …

Recently, neural machine translation (NMT) has been extended to multilinguality, that is to
handle more than one translation direction with a single system. Multilingual NMT showed …

This paper highlights the impressive utility of multi-parallel corpora for transfer learning in a
one-to-many low-resource neural machine translation (NMT) setting. We report on a …

The rapid growth of machine translation (MT) systems has necessitated comprehensive
studies to meta-evaluate evaluation metrics being used, which enables a better selection of …

Multilingual neural machine translation has shown the capability of directly translating
between language pairs unseen in training, ie zero-shot translation. Despite being …

Morphological modeling in neural machine translation (NMT) is a promising approach to
achieving open-vocabulary machine translation for morphologically-rich languages …

Indian language machine translation performance is hampered due to the lack of large scale
multi-lingual sentence aligned corpora and robust benchmarks. Through this paper, we …