A Neural Network Architecture for Multilingual Punctuation Generation
Miguel Ballesteros, Leo Wanner · 2016
Even syntactically correct sentences are perceived as awkward if they do not contain correct punctuation.Still, the problem of automatic generation of punctuation marks has been largely neglected for a long time.We present a novel model that introduces punctuation marks into raw text material with transition-based algorithm using LSTMs.Unlike the state-of-the-art approaches, our model is language-independent and also neutral with respect to the intended use of the punctuation.Multilingual experiments show that it achieves high accuracy on the full range of punctuation marks across languages.