Output details
11 - Computer Science and Informatics
University of Oxford
Output title
A discriminative latent variable model for statistical machine translation
Type
E - Conference contribution
DOI
-
Name of conference/published proceedings
ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference
Volume number
-
Issue number
-
First page of article
200
ISSN of proceedings
-
Year of publication
2008
Number of additional authors
2
Additional information
<22>
This paper introduced a learning algorithm that is able to tractably marginalise in polynomial time the exponential number of equivalent derivations that occur in a machine translation system. This algorithm was then used to conduct the first large scale discriminative learning experiments for a probabilistic machine translation model with millions of features, thus establishing the now dominant learning paradigm for such models. The Conference of the ACL is the highest ranked publication venue in Computational Linguistics (Google Scholar Metrics) and ACL2008 had an acceptance rate of 25%.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
17
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
