Sciweavers

Share
ACL
2010

Diversify and Combine: Improving Word Alignment for Machine Translation on Low-Resource Languages

8 years 10 months ago
Diversify and Combine: Improving Word Alignment for Machine Translation on Low-Resource Languages
We present a novel method to improve word alignment quality and eventually the translation performance by producing and combining complementary word alignments for low-resource languages. Instead of focusing on the improvement of a single set of word alignments, we generate multiple sets of diversified alignments based on different motivations, such as linguistic knowledge, morphology and heuristics. We demonstrate this approach on an English-to-Pashto translation task by combining the alignments obtained from syntactic reordering, stemming, and partial words. The combined alignment outperforms the baseline alignment, with significantly higher F-scores and better translation performance.
Bing Xiang, Yonggang Deng, Bowen Zhou
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Bing Xiang, Yonggang Deng, Bowen Zhou
Comments (0)
books