For efficiency considerations, state-of-theart neural machine translation (NMT) requires the
vocabulary to be restricted to a limited-size set of several thousand symbols. This is highly …

The current state-of-the-art in statistical machine translation (SMT) suffers from issues of
sparsity and inadequate modeling power when translating into morphologically rich …

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 …

Sign languages represent an interesting niche for statistical machine translation that is
typically hampered by the scarceness of suitable data, and most papers in this area apply …

Compounding is a highly productive word-formation process in some languages that is often
problematic for natural language processing applications. In this paper, we investigate …

Compound splitting is an important problem in many NLP applications which must be solved
in order to address issues of data sparsity. Previous work has shown that linguistic …

Most of the text in a computer program is composed of the names of variables and functions.
These names are selected by one developer, and need to be understood by others. This is …

The contribution discusses variants of architectures of hybrid MT systems. The three main
types of architectures are: coupling of systems (serial or parallel), architecture adaptations …

Machine Translation denotes the translation of a text written in one language into another
language performed by a computer program. In times of internet and globalisation, there has …

Abstract English to Indian language machine translation poses the challenge of structural
and morphological divergence. This paper describes English to Indian language statistical …