Improving the accuracy of English-Arabic statistical sentence alignment

: Multilingual natural language processing systems are increasingly relying on parallel corpus to ameliorate their output. Parallel corpora constitute the basic block for training a statistical natural language processing system and creating translation and language models. Several systems have been devised that automatically align words of a pair of sentences, each in a language. Such systems have been used successfully with European languages. In this paper, one such system is used to align sentences in an English-Arabic corpus. The system works poorly given raw unaligned sentence English-Arabic sentence pairs. This prompted the development of a preprocessing step to be applied to the Arabic sentences. The same corpus was then preprocessed and a significant improvement is reported when alignment is attempted using the preprocessed unaligned sentences.

• Type: Journal
• Year: 2011
• Where: IAJIT
• Authors: Mohammad Salameh, Rached Zantout, Nashat Mansour
• Keywords: Distributed And Parallel Computing, IAJIT 2011, Natural Language Processing, Statistical Natural Language Processing, Unaligned Sentences