Models of morphosyntax for statistical machine translation

• Applicant: Professor Dr. Hinrich Schütze
• Subject Area: General and Comparative Linguistics, Experimental Linguistics, Typology, Non-European Languages
• Term: from 2009 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 123083856

• Final Report Year: 2018

Final Report Abstract

The project resulted in a large number of scientific innovations. Papers about these innovations were published in some of the best conferences and journals in natural language processing. Particularly important advances were: - The ability to integrate classification models into SMT decoders. - Classification models for inflectional and syntactic choice in all phrase-based, hierarchical and syntax-based SMT. - Reaching the capability of generating unseen inflected forms in SMT. Important source code was published in both the open source Moses toolkit, and on our own local repository: http://cistern.cis.lmu.de There were no major deviations in the project plan and all workpackages were carried out successfully.