Text cleaning with transformer language models for Hungarian
In language technology, clean data is fundamental for training high-quality models, yet large corpora often contain substantial noise due to OCR errors, missing diacritics, and various user-generated inconsistencies. This paper presents a comprehensive text cleaning pipeline tailored for Hungarian,...
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| Dokumentumtípus: | Könyv része |
| Megjelent: |
Szegedi Tudományegyetem TTIK, Informatikai Intézet
Szeged
2025
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| Sorozat: | Magyar Számítógépes Nyelvészeti Konferencia
21 |
| Kulcsszavak: | Nyelvi modell, Nyelvészet - számítógép alkalmazása |
| Tárgyszavak: | |
| Online Access: | http://acta.bibl.u-szeged.hu/88777 |
| Tartalmi kivonat: | In language technology, clean data is fundamental for training high-quality models, yet large corpora often contain substantial noise due to OCR errors, missing diacritics, and various user-generated inconsistencies. This paper presents a comprehensive text cleaning pipeline tailored for Hungarian, leveraging transformer-based language models optimized for three key tasks: OCR error correction, diacritic restoration, and filtering grammatically incorrect sentences. We introduce huT5, a Hungarian adaptation of the mT5 model, which significantly reduces model parameters and resource demands while maintaining strong performance on Hungarian-specific text cleaning tasks. The huT5 models were fine-tuned on carefully constructed Hungarian corpora for each task and benchmarked against state-of-the-art methods, demonstrating competitive results, particularly in OCR error correction and diacritic restoration. Our pipeline offers an efficient, freely accessible solution to enhance data quality for Hungarian NLP applications, setting a new standard in resource-efficient, language-specific text cleaning. |
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| Terjedelem/Fizikai jellemzők: | 123-135 |
| ISBN: | 978-963-688-034-7 |