Punctuation Prediction for Polish Texts using Transformers
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Abstract (arXiv)
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.
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References · 5
- 2017Attention Is All You Needcited by 59,932
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2021HerBERT: Efficiently Pretrained Transformer-based Language Model for Polishcited by 51
- 2020Pre-training Polish Transformer-based Language Models at Scalecited by 21
- 2020Robust Prediction of Punctuation and Truecasing for Medical ASRcited by 16
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