An approach to automatic acquisition of translation templates based on phrase structure extraction and alignment

In this paper, we propose a new approach for automatically acquiring translation templates from unannotated bilingual spoken language corpora. Two basic algorithms are adopted: a grammar induction algorithm, and an alignment algorithm using bracketing transduction grammar. The approach is unsupervised, statistical, and data-driven, and employs no parsing procedure. The acquisition procedure consists of two steps. First, semantic groups and phrase structure groups are extracted from both the source language and the target language. Second, an alignment algorithm based on bracketing transduction grammar aligns the phrase structure groups. The aligned phrase structure groups are post-processed, yielding translation templates. Preliminary experimental results show that the algorithm is effective.