The present article investigates the fusion of different language models to improve
translation accuracy. A hybrid MT system, recentlydeveloped in the European …

This thesis presents the design and implementation of linguistically-informed models for
statistical phrase-based machine translation. Using Koehn's Pharaoh (2004), a state-of-the …

The present article reports on efforts to improve the translation accuracy of a corpus―based
Machine Translation (MT) system. In order to achieve that, an error analysis performed on …

The current paper presents a languageindependent methodology, which facilitates the
creation of machine translation (MT) systems for various language pairs. This methodology …

–Simple (naïve) modeling of the language translation problem!–Cannot model and generate
the correct translation for many linguistic phenomena across languages–both common and …

The merits of combining the positive elements of the rule-based and data-driven approaches
to MT are clear: a combined model has the potential to be highly accurate, robust, cost …

Rule-based approaches have been the dominant paradigm in developing MT systems. Such
approaches, however, suffer from difficulties in knowledge acquisition to meet the wide …

Translation models used for statistical machine translation are compiled from parallel
corpora; such corpora are manually translated, but the direction of translation is usually …

In this paper we describe the statistical machine translation system of the RWTH Aachen
University developed for the translation task of the Fifth Workshop on Statistical Machine …

Abstract Natural Language Processing (NLP) is the field of Artificial Intelligence research
that aims to teach computers to produce and understand human text and speech. Major …