An automatic model and Gold Standard for translation alignment of Ancient Greek

• Autor(a) principal: Yousef, Tariq
• Data de Publicação: 2022
• Outros Autores: Palladino, Chiara, Shamsian, Farnoosh, Ferreira, Anise d'Orange [UNESP], Reis, Michel Ferreira dos [UNESP], Mariani, J, Calzolari, N., Bechet, F., Blache, P., Choukri, K., Cieri, C., Declerck, T., Goggi, S., Isahara, H., Maegaard, B., Mazo, H., Odijk, H., Piperidis, S.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/245136
• topic: Translation Alignment; Gold Standard; Alignment Guidelines; Ancient Greek

This paper illustrates a workflow for developing and evaluating automatic translation alignment models for Ancient Greek. We designed an annotation Style Guide and a gold standard for the alignment of Ancient Greek-English and Ancient Greek-Portuguese, measured inter-annotator agreement and used the resulting dataset to evaluate the performance of various translation alignment models. We proposed a fine-tuning strategy that employs unsupervised training with mono- and bilingual texts and supervised training using manually aligned sentences. The results indicate that the fine-tuned model based on XLM-Roberta is superior in performance, and it achieved good results on language pairs that were not part of the training data.