NL4AI 2021 (AIxIA) Paper

Our paper ‘Evaluating Transformer Models for Punctuation Restoration in Italian’ (with Andrea Amelio Ravelli and Felice Dell’Orletta) has been accepted at the NL4AI Workshop (AIxIA Conference). In this paper, we propose an evaluation of a Transformer-based punctuation restoration model for the Italian language. Experimenting with a BERT-base model, we perform several fine-tuning with different training data and sizes and tested them in an in- and cross-domain scenario. Moreover, we offer a comparison in a multilingual setting with the same model fine-tuned on English transcriptions. Finally, we conclude with an error analysis of the main weaknesses of the model related to specific punctuation marks.