Bilingual phrase-to-phrase alignment for arbitrarily-small datasets

This paper presents a novel system for sub-sentential alignment of bilingual sentence pairs, however few, using readily-available machine-readable bilingual dictionaries. Performance is evaluated against an existing gold-standard parallel corpus where word alignments are annotated, showing results that are a considerable improvement on a comparable system and on GIZA++ performance for the same corpus. Since naïve application of the system for N languages would require N(N 1) dictionaries, it is also evaluated using a pivot language, where only 2(N 1) dictionaries would be required, with surprisingly similar performance. The system is proposed as an alternative to statistical methods, for use with very small corpora or for ‘on-the-fly’ alignment.