The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
An efficient method for determining bilingual word classes
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
A DP based search using monotone alignments in statistical translation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
A DP based search algorithm for statistical machine translation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Word re-ordering and DP-based search in statistical machine translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Improving SMT quality with morpho-syntactic analysis
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A comparison of alignment models for statistical machine translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
HMM-based word alignment in statistical translation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Translation with cascaded finite state transducers
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Candide system for machine translation
HLT '94 Proceedings of the workshop on Human Language Technology
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
Stochastic modelling: from pattern classification to language translation
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
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This paper gives an overview of our work on statistical machine translation of spoken dialogues, in particular in the framework of the VERBMOBIL project. The goal of the VERBMOBIL project is the translation of spoken dialogues in the domains of appointment scheduling and travel planning. Starting with the Bayes decision rule as in speech recognition, we show how the required probability distributions can be structured into three parts: the language model, the alignment model and the lexicon model. We describe the components of the system and report results on the VERBMOBIL task. The experience obtained in the VERBMOBIL project, in particular a large-scale end-to-end evaluation, showed that the statistical approach resulted in significantly lower error rates than three competing translation approaches: the sentence error rate was 29% in comparison with 52% to 62% for the other translation approaches.