A maximum entropy approach to natural language processing
Computational Linguistics
A systematic comparison of various statistical alignment models
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Relabeling syntax trees to improve syntax-based machine translation quality
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Continuous space language models for statistical machine translation
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Improved language modeling for statistical machine translation
ParaText '05 Proceedings of the ACL Workshop on Building and Using Parallel Texts
Segmentation for English-to-Arabic statistical machine translation
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Syntactic phrase reordering for English-to-Arabic statistical machine translation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Syntactic reordering for English-Arabic phrase-based machine translation
Semitic '09 Proceedings of the EACL 2009 Workshop on Computational Approaches to Semitic Languages
| Hi-index | 0.00 |
We present a joint morphological-lexical language model (JMLLM) for use in statistical machine translation (SMT) of language pairs where one or both of the languages are morphologically rich. The proposed JMLLM takes advantage of the rich morphology to reduce the Out-Of-Vocabulary (OOV) rate, while keeping the predictive power of the whole words. It also allows incorporation of additional available semantic, syntactic and linguistic information about the morphemes and words into the language model. Preliminary experiments with an English to Dialectal-Arabic SMT system demonstrate improved translation performance over trigram based baseline language model.