Paraphrase Lattice for Statistical Machine Translation

Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the translation of German because it can handle input ambiguities such as speech recognition ambiguities and German word segmentation ambiguities. We show that lattice decoding is also useful for handling input variations. Given an input sentence, we build a lattice which represents paraphrases of the input sentence. We call this a paraphrase lattice. Then, we give the paraphrase lattice as an input to the lattice decoder. The decoder selects the best path for decoding. Using these paraphrase lattices as inputs, we obtained significant gains in BLEU scores for IWSLT and Europarl datasets.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Takashi Onishi, Masao Utiyama, Eiichiro Sumita
• Keywords: ACL 2010, Computational Linguistics, Input, Paraphrase, Paraphrase Lattice