A neural network architecture for multilingual punctuation generation
A neural network architecture for multilingual punctuation generation
Citació
- Ballesteros M, Wanner L. A neural network architecture for multilingual punctuation generation. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing; 2016 Nov. 1-5; Austin (TX, USA). [place unknown]: ACL; 2016. p. 1048-53
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Resum
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/npresent 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.