Abstract. Parallel texts are enriched by alignment algorithms, thus establishing a relationship between the structures of the implied languages. Depending on the alignment level, t...
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
We describe a novel approach to machine translation that combines the strengths of the two leading corpus-based approaches: Phrasal SMT and EBMT. We use a syntactically informed d...
This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 t...
Thorsten Brants, Ashok C. Popat, Peng Xu, Franz Jo...
We propose a new probabilistic approach to information retrieval based upon the ideas and methods of statistical machine translation. The central ingredient in this approach is a ...