Terminological resources have proven necessary in many organizations and institutions to ensure communication between experts. However, the maintenance of these resources is a very time-consuming and expensive process. ...

Knowledge graphs and ontologies underpin many natural language processing applications, and to apply these to new languages, these knowledge graphs must be translated. Up until now, this has been achieved either by direct ...

Machine translation between closely related languages is less challenging and exhibits a smaller number of translation errors than translation between distant languages, but there are still obstacles which should be ...

Wordnets are extensively used in natural language processing, but the current approaches for manually building a wordnet from scratch involves large research groups for a long period of time, which are typically not ...

We present a freely available corpus containing source language texts from different domains along with their automatically generated translations into several distinct morphologically rich languages, their post-edited ...

The META-NET research on language technologies in 2012 showed a weak support on tools for crossing the language barrier for many European languages, including the south Slavic languages. Therefore, we describe a statistical ...

In this paper, we address the problem of extracting and integrating bilingual terminology into a Statistical Machine Translation (SMT) system for a Computer Aided Translation (CAT) tool scenario. We develop a framework ...

The automatic translation of domain-specific documents is often a hard task for generic Statistical Machine Translation (SMT) systems, which are not able to correctly translate the large number of terms encountered in the ...

Multimodal machine translation is the task of translating from a source text into the target language using information from other modalities. Existing multimodal datasets have been restricted to only highly resourced ...