Experiments with a Hindi-to-English transfer-based MT system under a miserly data scenario
ACM Transactions on Asian Language Information Processing (TALIP)
Hebrew Computational Linguistics: Past and Future
Artificial Intelligence Review
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Effective phrase translation extraction from alignment models
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
An unsupervised morpheme-based HMM for hebrew morphological disambiguation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Scalable inference and training of context-rich syntactic translation models
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Example-based machine translation based on syntactic transfer with statistical models
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
A finite-state morphological grammar of hebrew
Natural Language Engineering
Exploiting Parallel Treebanks to Improve Phrase-Based Statistical Machine Translation
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
Decoding with syntactic and non-syntactic phrases in a syntax-based machine translation system
SSST '09 Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation
Statistical transfer systems for French--English and German--English machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
An improved statistical transfer system for French--English machine translation
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Fine-tuning in Brazilian Portuguese--English statistical transfer machine translation: verbal tenses
HLT-SRWS '10 Proceedings of the NAACL HLT 2010 Student Research Workshop
Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
Agreement constraints for statistical machine translation into German
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Machine translation between Hebrew and Arabic
Machine Translation
Syntactic structure transfer in a tamil to hindi MT system – a hybrid approach
CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
Incorporating linguistic knowledge in statistical machine translation: translating prepositions
HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
| Hi-index | 0.00 |
The CMU Statistical Transfer Framework (Stat-XFER) is a general framework for developing search-based syntax-driven machine translation (MT) systems. The framework consists of an underlying syntax-based transfer formalism along with a collection of software components designed to facilitate the development of a broad range of MT research systems. Themain components are a general language-independent runtime transfer engine and decoder, along with several different tools for creating the various underlying language-pair-specific resources that are required for building a specific MT system for any given language pair.We describe the general framework, its unique properties and features, and its application to the construction of MT research prototype systems for a diverse collection of language pairs.