Empirical Methods for Compound Splitting

2003, English, 7 pages, .ps, .pdf. Published at EACL 2003 at Budapest, Hungary.

Compounded words are a challenge for NLP applications such as machine translation (MT). We introduce methods to learn splitting rules from monolingual and parallel corpora. We evaluate them against a gold standard and measure their impact on performance of statistical MT systems. Results show accuracy of 99.1% and performance gains for MT of 0.039 BLEU on a German-English noun phrase translation task.