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, D'Orange Ferreira, Anise [UNESP], dos Reis, Michel Ferreira [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/246506
• topic: Alignment Guidelines; Ancient Greek; Gold Standard; Translation Alignment; Alignment guideline; Ancient Greeks; Automatic modeling; Automatic translation; Fine tuning; Gold standards; Performance; Style guides; Translation alignment; Work-flows

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.