8 Translation Technologies

Sunoikisis Digital Classics, Fall 2020

Session 8. Translation Technologies

Thursday November 26, 16:00 UK = 17:00 CET

Convenors: Franziska Naether (Leipzig), Chiara Palladino (Furman)

YouTube link: https://youtu.be/FzOvKMnqLaM

Slides: tba

Session outline

• Introduction: translation technologies
• Principles and theoretical aspects of text alignment
• Available tools for text alignment
• Applications: automatic translation alignment, graph databases, dynamic lexicon
• Live Demo of Ugarit with the Digital Rosetta Stone Project
• Presentation of the exercise

Seminar readings

• (two OA chapters will be selected from the list below later; all suggestions below please)

Further reading

• Gregory Crane (2019), "Beyond Translation: Language Hacking and Philology." Harvard Data Science Review 1.2. Available: https://doi.org/10.1162/99608f92.282ad764
• Philipp Koehn (2009). Statistical Machine Translation, Chapter 4: “Word-Based Models.” Cambridge University Press
• Despoina Panou (2013). “Equivalence in Translation Theories: A Critical Evaluation, Theory and Practice.” Language Studies 3.1, pp. 1-6. Available: http://www.academypublication.com/issues/past/tpls/vol03/01/01.pdf
• Tamara Pataridze & Bastien Kindt (2018). "Text Alignment in Ancient Greek and Georgian: A Case-Study on the First Homily of Gregory of Nazianzus." Journal of Data Mining and Digital Humanities. Available: https://jdmdh.episciences.org/4182/pdf
• Raquel de Pedro (1999). The Translatability of Texts: A Historical Overview. Meta, XLIV, 4, 1999. Available: http://www3.uji.es/~aferna/EA0921/4a-Translatability.pdf

Other resources

• Ugarit iAligner
• Digital Rosetta Stone project
• “The Digital Rosetta Stone: textual alignment and linguistic annotation.” (Slides by Monica Berti, Julia Jushaninowa, Franziska Naether, Giuseppe G. A. Celano, Polina Yordanova.) Available: https://www.academia.edu/25184052/The_Digital_Rosetta_Stone_Textual_Alignment_and_Linguistic_Annotation

Exercise

• Go on Ugarit and create a bilingual alignment of a parallel corpus of your choice (or feel free to use our suggestion: Bible parallel corpus in different languages: https://github.com/SunoikisisDC/SunoikisisDC-2019-2020/tree/master/2020-Digital-Classics-slides/Translation%20Alignment/data/txt). Choose two languages that you are familiar with and focus on the differences across translation: what words align perfectly? What words align imperfectly, or not at all? What words are missing across the two texts? What is the overall percentage of matches?
• After you have completed the bilingual alignment, choose a parallel text in a third language that you do not know and perform a trilingual alignment. See how much of the third language you can align, by using the two other languages as an aid for better understanding.