Linguistically Enriched Word-Sequence Kernels for Discriminative Language Modeling
Linguistically Enriched Word-Sequence Kernels for Discriminative Language Modeling
This chapter introduces a method for taking advantage of background linguistic resources in statistical machine translation. It starts with a brief introduction to word-sequence kernels, followed by a description of the notion of factored representation and details of the kernel formulation. The next section validates the kernel construction on an artificial discrimination task reproducing some of the conditions encountered in translation. The chapter concludes with a discussion of related and future work.
Keywords: statistical machine translation, word-sequence kernels, factored representation, kernel construction
MIT Press Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs, and if you can't find the answer there, please contact us.