An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Towards interactive text understanding
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Multi-engine machine translation with voted language model
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
N-gram-based Machine Translation
Computational Linguistics
Word lattices for multi-source translation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Lattice Minimum Bayes-Risk decoding for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A unigram orientation model for statistical machine translation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Domain adaptation for statistical machine translation with monolingual resources
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
System Combination for Machine Translation of Spoken and Written Language
IEEE Transactions on Audio, Speech, and Language Processing
Character-based pivot translation for under-resourced languages and domains
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Journal of Artificial Intelligence Research
WSD for n-best reranking and local language modeling in SMT
SSST-6 '12 Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation
Lattice BLEU oracles in machine translation
ACM Transactions on Speech and Language Processing (TSLP)
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We present a framework where auxiliary MT systems are used to provide lexical predictions to a main SMT system. In this work, predictions are obtained by means of pivoting via auxiliary languages, and introduced into the main SMT system in the form of a low order language model, which is estimated on a sentence-by-sentence basis. The linear combination of models implemented by the decoder is thus extended with this additional language model. Experiments are carried out over three different translation tasks using the European Parliament corpus. For each task, nine additional languages are used as auxiliary languages to obtain the triangulated predictions. Translation accuracy results show that improvements in translation quality are obtained, even for large data conditions.