In this paper, we focus on the use of Arabic transliteration to improve the results of a linguistics-based word alignment approach from parallel text corpora. This approach uses, on the one hand, a bilingual lexicon, named entities, cognates and grammatical tags to align single words, and on the other hand, syntactic dependency relations to align compound words. We have evaluated the word aligner integrating Arabic transliteration using two methods: A manual evaluation of the alignment quality and an evaluation of the impact of this alignment on the translation quality by using the Moses statistical machine translation system. The obtained results show that Arabic transliteration improves the quality of both alignment and translation.