A systematic comparison of various statistical alignment models
Computational Linguistics
Empirical methods for compound splitting
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Decompounding query keywords from compounding languages
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StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Initial explorations in English to Turkish statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Statistical machine translation of german compound words
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Improving alignment for SMT by reordering and augmenting the training corpus
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
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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
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Shallow semantic trees for SMT
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Hierarchical Bayesian language modelling for the linguistically informed
EACL '12 Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics
Generation of compound words in statistical machine translation into compounding languages
Computational Linguistics
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In this article, compound processing for translation into German in a factored statistical MT system is investigated. Compounds are handled by splitting them prior to training, and merging the parts after translation. I have explored eight merging strategies using different combinations of external knowledge sources, such as word lists, and internal sources that are carried through the translation process, such as symbols or parts-of-speech. I show that for merging to be successful, some internal knowledge source is needed. I also show that an extra sequence model for part-of-speech is useful in order to improve the order of compound parts in the output. The best merging results are achieved by a matching scheme for part-of-speech tags.