In this paper we present a confidence measure for word alignment based on the posterior probability of alignment links. We introduce sentence alignment confidence measure and alignment link confidence measure. Based on these measures, we improve the alignment quality by selecting high confidence sentence alignments and alignment links from multiple word alignments of the same sentence pair. Additionally, we remove low confidence alignment links from the word alignment of a bilingual training corpus, which increases the alignment F-score, improves Chinese-English and Arabic-English translation quality and significantly reduces the phrase translation table size.