Thea Sommerschield: Machine Learning for Ancient Languages. Trends, challenges, and future prospects for a digital ancient history
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2 février 2024
- doi: 10.58079/vqpa
info:eu-repo/semantics/openAccess
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digitalhistory, « Thea Sommerschield: Machine Learning for Ancient Languages. Trends, challenges, and future prospects for a digital ancient history », Digital History Berlin, ID : 10.58079/vqpa
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Recent advances in Artificial Intelligence and Machine Learning (ML) have facilitated unprecedented analyses of ancient languages with unparalleled detail. ML methods now enable the exploration of several tasks associated with the study of ancient texts, including decipherment, digitization, attribution, studies in intertextuality and semantics. This talk will provide an overview of key tasks, trends, and transformations within the multifaceted realm of ML for Ancient Languages, drawing...