CroVeWA: Crosslingual Vector-Based Writing Assistance

Hubert Soyer, Goran Topic, Pontus Stenetorp, Akiko Aizawa

Abstract: We present an interactive web-based writing assistance system that is based on recent advances in crosslingual compositional distributed semantics. Given queries in Japanese or English, our system can retrieve semantically related sentences from high quality English corpora. By employing crosslingually constrained vector space models to represent phrases, our system naturally sidesteps several difficulties that would arise from direct word-to-text matching, and is able to provide novel functionality like the visualization of semantic relationships between phrases interlingually and intralingually.