Improving Machine Translation via Triangulation and Transliteration
نویسندگان
چکیده
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.
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