MOOD: A Modular Object-Oriented Decoder for Statistical Machine Translation

Alexandre Patry, Fabrizio Gotti, Philippe Langlais

Abstract: We present an Open Source framework called MOOD developed in order tofacilitate the development of a Statistical Machine Translation Decoder.MOOD has been modularized using an object-oriented approach which makes itespecially suitable for the fast development of state-of-the-art decoders. Asa proof of concept, a clone of the pharaoh decoder has been implemented andevaluated. This clone named ramses is part of the current distribution of MOOD.