Punctuation Prediction for Polish Texts using Transformers
<|reference_start|>Punctuation Prediction for Polish Texts using Transformers: Speech recognition systems typically output text lacking punctuation. However, punctuation is crucial for written text comprehension. To tackle this problem, Punctuation Prediction models are developed. This paper describes a solution for Poleval 2022 Task 1: Punctuation Prediction for Polish Texts, which scores 71.44 Weighted F1. The method utilizes a single HerBERT model finetuned to the competition data and an external dataset.<|reference_end|>
@article{pokrywka2024punctuation,
    title={Punctuation Prediction for Polish Texts using Transformers},
    author={Jakub Pokrywka},
    journal={Proceedings of the 18th Conference on Computer Science and
  Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. \'Sl\k{e}zak
  (eds). ACSIS, Vol. 35, pages 1251-1254 (2023)},
    year={2024},
    doi={10.15439/2023F1633},
    archivePrefix={arXiv},
    eprint={2410.04621},
    primaryClass={cs.CL}
}