Automatic punctuation restoration with BERT models

01/18/2021

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by   Attila Nagy, et al.

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We present an approach for automatic punctuation restoration with BERT models for English and Hungarian. For English, we conduct our experiments on Ted Talks, a commonly used benchmark for punctuation restoration, while for Hungarian we evaluate our models on the Szeged Treebank dataset. Our best models achieve a macro-averaged F_1-score of 79.8 in English and 82.2 in Hungarian. Our code is publicly available.