@inproceedings{janssen-etal-2025-alignment,
    title = "Alignment of Historical Manuscript Transcriptions and Translations",
    author = "Janssen, Maarten  and
      Lendvai, Piroska  and
      Jouravel, Anna",
    editor = "Angelova, Galia  and
      Kunilovskaya, Maria  and
      Escribe, Marie  and
      Mitkov, Ruslan",
    booktitle = "Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/corrections-2026-01/2025.ranlp-1.55/",
    pages = "462--470",
    abstract = "Using an XML-based framework, we compiled a gold standard for alignments in five primary as well as derived texts, related to \textit{De Lepra ad Sistelium} by Methodius Olympius. These comprise diplomatic transcripts, editions, and translations of this work, involving both historical and modern languages. Using the TEITOK corpus platform, we created sentence-level gold standard alignments for our parallel resp. comparable texts, and applied both neural and classical alignment methods (SentenceBERT, Hunalign, Awesome-Align). We evaluated the methods in terms of Alignment Error Rate. We show that for alignment of our historical texts, Hunalign performs better than deep learning based methods."
}