Parallel fragments : Measuring their impact on translation performance

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• 作者：Sadaf Abdul-Rauf^a ; ^b ; ^{sadaf.abdulrauf@gmail.com} ; Holger Schwenk^b ; Mohammad Nawaz^c
• 关键词：Parallel fragments ; Statistical machine translation ; Comparable corpus
• 刊名：Computer Speech & Language
• 出版年：2017
• 出版时间：May 2017
• 年：2017
• 卷：43
• 期：Complete
• 页码：56-69
• 全文大小：862 K
• 卷排序：43

文摘

Phrase fragments have proved to be a valuable resource for increasing translation and natural language generation performance. A novel approach to find parallel fragments from comparable corpora is presented which is simple and efficient in processing. Difference in translation improvement for fragments extracted from related versus non related corpus is presented. Comparison of impact of parallel fragments vs. sentences is reported highlighting the significance of parallel segments. Proposed approach is compared theoretically with an earlier approach on all phases of the fragment extraction pipeline.