Improving machine translation via triangulation and transliteration
Nadir Durrani, Philipp Koehn · Edinburgh Research Explorer (University of Edinburgh) · 2014
In this paper we improve Urdu→Hindi-English machine translation through triangulation and transliteration. First we built an Urdu→Hindi SMT system by inducing triangulated and transliterated phrase-tables from Urdu–English and Hindi–English phrase translation models. We then use it to translate the Urdu part of the Urdu-English parallel data into Hindi, thus creating an artificial Hindi-English parallel data. Our phrase-translation strategies give an improvement of up to +3.35 BLEU points over a baseline Urdu→Hindi system. The synthesized data improve Hindi→English system by +0.35 and English→Hindi system by +1.0 BLEU points.