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Computational Linguistics
Empirical methods for compound splitting
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StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Statistical machine translation of german compound words
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PaIR '10 Proceedings of the 3rd international workshop on Patent information retrieval
Pre- and postprocessing for statistical machine translation into Germanic languages
HLT-SS '11 Proceedings of the ACL 2011 Student Session
Productive generation of compound words in statistical machine translation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Algorithms for the verification of the semantic relation between a compound and a given lexeme
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EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
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WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Generation of compound words in statistical machine translation into compounding languages
Computational Linguistics
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An empirical method for splitting German compounds is explored by varying it in a number of ways to investigate the consequences for factored statistical machine translation between English and German in both directions. Compound splitting is incorporated into translation in a preprocessing step, performed on training data and on German translation input. For translation into German, compounds are merged based on part-of-speech in a postprocessing step. Compound parts are marked, to separate them from ordinary words. Translation quality is improved in both translation directions and the number of untranslated words in the English output is reduced. Different versions of the splitting algorithm performs best in the two different translation directions.