Improving machine translation via triangulation and transliteration

Nadir Durrani, Philipp Koehn

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of 17th Annual conference of the European Association for Machine Translation
Pages71-78
Number of pages8
Publication statusPublished - 2014

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    • EU-Bridge

      Renals, S. (Principal Investigator), King, S. (Co-investigator), Koehn, P. (Co-investigator) & Osborne, M. (Co-investigator)

      EU government bodies

      1/02/12 → 31/01/15

      Project: Research

    • MateCat - Machine Translation Enhanced Computer Assited Translation

      Koehn, P. (Principal Investigator)

      EU government bodies

      1/11/11 → 31/10/14

      Project: Research

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