Archeology: Restoring ancient texts using artificial intelligence
A paper suggesting that up to 72% accuracy can be achieved when multiple historians use deep neural networks trained to restore ancient Greek inscriptions will be published in Nature this week.The findings of this study help restore newly discovered and obscure inscriptions and estimate their age and location by increasing speed and accuracy, helping to understand ancient history. It may be possible to proceed.
Historians are studying inscriptions written directly by people of the past on the materials (stones, pottery, metals, etc.) that remain to this day in order to elucidate the history of ancient civilization.However, many inscriptions have been damaged for centuries and are now unreadable and uncertain when they were created.Epigraphers who are experts in epigraphy can restore missing text, but their traditional methods are very complex and require a great deal of time.
Now, Yannis Assael and Thea Sommerschield are a type of artificial intelligence trained to restore ancient Greek inscriptions and estimate their age and location to overcome the limitations of current epigraphy methods. We verified a deep neural network (named "Isaka"). Assael et al. Revealed that 62% accuracy was achieved when restoring inscriptions damaged by Isaka alone, and 72% accuracy was achieved when multiple historians used Isaka.It also revealed that Isaka could help identify where and when the inscription was created.In the experiments in this study, Isaka estimated the location of the inscription with 71% accuracy, and the date of creation was within less than 30 years from the date of creation proposed by historians.
The findings of this study may open up the possibility of collaboration between artificial intelligence and historians, leading to further elucidation of human history.
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* This article is reprinted from "Nature Japan Featured Highlights".
Reprinted from: "Archeology: Restoration of inscriptions using artificial intelligence'