Data Cleaning for Word Alignment

10 years 9 months ago
Data Cleaning for Word Alignment
Parallel corpora are made by human beings. However, as an MT system is an aggregation of state-of-the-art NLP technologies without any intervention of human beings, it is unavoidable that quite a few sentence pairs are beyond its analysis and that will therefore not contribute to the system. Furthermore, they in turn may act against our objectives to make the overall performance worse. Possible unfavorable items are n : m mapping objects, such as paraphrases, non-literal translations, and multiword expressions. This paper presents a pre-processing method which detects such unfavorable items before supplying them to the word aligner under the assumption that their frequency is low, such as below 5 percent. We show an improvement of Bleu score from 28.0
Tsuyoshi Okita
Added 16 Feb 2011
Updated 16 Feb 2011
Type Journal
Year 2009
Where ACL
Authors Tsuyoshi Okita
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