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» Improving Statistical Word Alignment with Ensemble Methods
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ACL
2009
13 years 5 months ago
Bridging Morpho-Syntactic Gap between Source and Target Sentences for English-Korean Statistical Machine Translation
Often, Statistical Machine Translation (SMT) between English and Korean suffers from null alignment. Previous studies have attempted to resolve this problem by removing unnecessar...
Gum-Won Hong, Seung-Wook Lee, Hae-Chang Rim
ACL
2012
11 years 10 months ago
Learning Better Rule Extraction with Translation Span Alignment
This paper presents an unsupervised approach to learning translation span alignments from parallel data that improves syntactic rule extraction by deleting spurious word alignment...
Jingbo Zhu, Tong Xiao, Chunliang Zhang
NAACL
2003
13 years 8 months ago
Unsupervised methods for developing taxonomies by combining syntactic and statistical information
This paper describes an unsupervised algorithm for placing unknown words into a taxonomy and evaluates its accuracy on a large and varied sample of words. The algorithm works by ï...
Dominic Widdows
COLING
2010
13 years 2 months ago
Discriminative Induction of Sub-Tree Alignment using Limited Labeled Data
We employ Maximum Entropy model to conduct sub-tree alignment between bilingual phrasal structure trees. Various lexical and structural knowledge is explored to measure the syntac...
Jun Sun, Min Zhang, Chew Lim Tan
ACL
2007
13 years 9 months ago
An Ensemble Method for Selection of High Quality Parses
While the average performance of statistical parsers gradually improves, they still attach to many sentences annotations of rather low quality. The number of such sentences grows ...
Roi Reichart, Ari Rappoport