Objective We investigate machine translation (MT) of user search queries in the context of
cross-lingual information retrieval (IR) in the medical domain. The main focus is on …

In this paper, we tackle the problem of domain adaptation of statistical machine translation
(SMT) by exploiting domain-specific data acquired by domain-focused crawling of text from …

Computer-assisted translation (CAT) has always used translation memories, which require
the translator to have a corpus of previous translations that the CAT software can use to …

This paper presents the participation of the Charles University team in the WMT 2014
Medical Translation Task. Our systems are developed within the Khresmoi project, a large …

Statističko strojno prevođenje temeljeno na frazama jedan je od mogućih pristupa
automatskom strojnom prevođenju. U radu su predložene metode za poboljšanje kvalitete …

Abstract Domain Adaptation in Machine Translation means to take a machine translation
system that is restricted to work in a specific context and to enable the system to translate …

We propose and study three different novel approaches for tackling the problem of
development set selection in Statistical Machine Translation. We focus on a scenario where …

Automatic translation of natural language is still (as of 2017) a long-standing but unmet
promise. While advancing at a fast rate, the underlying methods are still far from actually …

Statistical Machine Translation (SMT) is the task of automatic translation between two
natural languages (source language and target language) by using bilingual corpora. To …

Today, neural machine translation (NMT) systems constitute state-of-the-art systems in
machine translation. However, such translation models require relatively large train data and …