Tell your friends about this item:
Use of Source-language Context in Statistical Machine Translation: Integrating Source-language Context into the State-of-the-art Statistical Machine Translation Models
Rejwanul Haque
Use of Source-language Context in Statistical Machine Translation: Integrating Source-language Context into the State-of-the-art Statistical Machine Translation Models
Rejwanul Haque
The translation features typically used in state-of-the-art statistical machine translation (SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling directly into log-linear phrase-based SMT (PB-SMT) and hierarchical PB-SMT (HPB-SMT), and can positively influence the weighting and selection of target phrases, and thus improve translation quality. In this book we present novel approaches to incorporate source-language contextual modelling into the state-of-the-art SMT models in order to enhance the quality of lexical selection. We investigate the effectiveness of use of a range of contextual features, including lexical features of neighbouring words, part-of-speech tags, supertags, sentence-similarity features, dependency information, and semantic roles. We explored a series of language pairs featuring typologically different languages, and examined the scalability of our research to larger amounts of training data.
Media | Books Paperback Book (Book with soft cover and glued back) |
Released | February 9, 2012 |
ISBN13 | 9783847340973 |
Publishers | LAP LAMBERT Academic Publishing |
Pages | 228 |
Dimensions | 150 × 13 × 226 mm · 340 g |
Language | English |
See all of Rejwanul Haque ( e.g. Paperback Book )