The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

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 …

With the invention of deep learning concepts, Machine Translation (MT) migrated towards
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …

This paper reports on the shared tasks organized by the 20th IWSLT Conference. The
shared tasks address 9 scientific challenges in spoken language translation: simultaneous …

This paper describes the systems that we submitted to the WMT19 Machine Translation
robustness task. This task aims to improve MT's robustness to noise found on social media …

Integrating linguistic features has been widely utilized in statistical machine translation
(SMT) systems, resulting in improved translation quality. However, for low-resource …

Neural machine translation (NMT) models are able to partially learn syntactic information
from sequential lexical information. Still, some complex syntactic phenomena such as …

In this paper, we present nmtpy, a flexible Python toolkit based on Theano for training Neural
Machine Translation and other neural sequence-to-sequence architectures. nmtpy …

Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT).
Now based on PyTorch, Sockeye 3 provides faster model implementations and more …

Abstract Neural Machine Translation (NMT) has attracted growing interest in recent years for
its promising performance compared to traditional approaches such as Statistical Machine …