Abstract
This paper describes a novel target-side syntactic language model for phrase-based statistical machine translation, bilingual structured language model. Our approach represents a new way to adapt structured language models (Chelba and Jelinek, 2000) to statistical machine translation, and a first attempt to adapt them to phrasebased statistical machine translation. We propose a number of variations of the bilingual structured language model and evaluate them in a series of rescoring experiments. Rescoring of 1000-best translation lists produces statistically significant improvements of up to 0.7 BLEU over a strong baseline for Chinese-English, but does not yield improvements for ArabicEnglish.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
