Manawi: Using multi-word expressions and named entities to improve machine translation

Abstract We describe the Manawi 1 ( ) system submitted to the 2014 WMT translation shared task. We participated in the English-Hindi (EN-HI) and Hindi-English (HI-EN) language pair and achieved 0.792 for the Translation Error Rate (TER) score 2 for EN-HI, the lowest among the competing systems. Our main innovations are (i) the usage of outputs from NLP tools, viz. billingual multi-word expression extractor and named-entity recognizer to improve SMT quality and (ii) the introduction of a novel filter method based on sentence-alignment features. The Manawi system showed the potential of improving translation quality by incorporating multiple NLP tools within the MT pipeline