TY - GEN
T1 - Word alignment with stochastic bracketing linear inversion transduction grammar
AU - Saers, Markus
AU - Nivre, Joakim
AU - Wu, Dekai
PY - 2010
Y1 - 2010
N2 - The class of Linear Inversion Transduction Grammars (LITGs) is introduced, and used to induce a word alignment over a parallel corpus. We show that alignment via Stochastic Bracketing LITGs is considerably faster than Stochastic Bracketing ITGs, while still yielding alignments superior to the widely-used heuristic of intersecting bidirectional IBM alignments. Performance is measured as the translation quality of a phrase-based machine translation system built upon the word alignments, and an improvement of 2.85 BLEU points over baseline is noted for French-English.
AB - The class of Linear Inversion Transduction Grammars (LITGs) is introduced, and used to induce a word alignment over a parallel corpus. We show that alignment via Stochastic Bracketing LITGs is considerably faster than Stochastic Bracketing ITGs, while still yielding alignments superior to the widely-used heuristic of intersecting bidirectional IBM alignments. Performance is measured as the translation quality of a phrase-based machine translation system built upon the word alignments, and an improvement of 2.85 BLEU points over baseline is noted for French-English.
UR - https://www.scopus.com/pages/publications/84857620595
M3 - Conference Paper published in a book
AN - SCOPUS:84857620595
SN - 1932432655
SN - 9781932432657
T3 - NAACL HLT 2010 - Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference
SP - 341
EP - 344
BT - NAACL HLT 2010 - Human Language Technologies
T2 - 2010 Human Language Technologies Conference ofthe North American Chapter of the Association for Computational Linguistics, NAACL HLT 2010
Y2 - 2 June 2010 through 4 June 2010
ER -