Abstract
Accurate punctuation in written text enables unambiguous communication, minimizing the risk of misunderstandings. Conversely, faulty punctuation can confuse the intended meaning, posing challenges for the author. The existing literature offers a collection of systems and algorithms to assist users in writing tasks. However, those focusing on English tend to exhibit higher accuracy. Furthermore, most models for punctuation restoration yield results without offering insight into their decision-making processes. Therefore, this study evaluated state-of-the-art punctuation restoration models specifically for Brazilian Portuguese and incorporated the principles of explainable artificial intelligence to clarify their predictions transparently. The findings indicate that the models assessed achieved an accuracy comparable to those of their English-language counterparts.
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