Learning Common Grammar from Multilingual Corpus

We propose a corpus-based probabilistic framework to extract hidden common syntax across languages from non-parallel multilingual corpora in an unsupervised fashion. For this purpose, we assume a generative model for multilingual corpora, where each sentence is generated from a language dependent probabilistic contextfree grammar (PCFG), and these PCFGs are generated from a prior grammar that is common across languages. We also develop a variational method for efficient inference. Experiments on a non-parallel multilingual corpus of eleven languages demonstrate the feasibility of the proposed method.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Tomoharu Iwata, Daichi Mochihashi, Hiroshi Sawada
• Keywords: ACL 2010, Computational Linguistics, Corpus-based Probabilistic Framework, Multilingual Corpora, Non-parallel Multilingual Corpora