Unlocking the Secrets of Ancient Writing. The Parallel Lives of Michael Ventris and Linda Schele and the Decipherment of Mycenaean and Mayan Writing

Catalogue of an exhibition conducted in conjunction with the Eleventh International Mycenological Colloquium held at the University of Texas at Austin in 2000. This program features brief histories of the CIPEM Mycenological conferences and PASP, followed by comparative retrospectives on both Michael Ventris, who deciphered Linear B, and Linda Schele, who performed a similar feat for Mayan glyphs.Classic

A Translation of the Malia Altar Stone

This paper presents a translation of the Malia Altar Stone inscription (CHIC 328), which is one of the longest known Cretan Hieroglyph inscriptions. The translation uses a synoptic transliteration to several scripts that are related to the Malia Altar Stone script. The synoptic transliteration strengthens the derived phonetic values and allows avoiding certain errors that would result from reliance on just a single transliteration. The synoptic transliteration is similar to a multiple alignment of related genomes in bioinformatics in order to derive the genetic sequence of a putative common ancestor of all the aligned genomes

A Computational Translation of the Phaistos Disk

For over a century the text of the Phaistos Disk remained an enigma without a convincing translation. This paper presents a novel semi-automatic translation method that uses for the first time a recently discovered connection between the Phaistos Disk symbols and other ancient scripts, including the Old Hungarian alphabet. The connection between the Phaistos Disk script and the Old Hungarian alphabet suggested the possibility that the Phaistos Disk language may be related to Proto-Finno-Ugric, Proto-Ugric, or Proto-Hungarian. Using words and suffixes from those languages, it is possible to translate the Phaistos Disk text as an ancient sun hymn, possibly connected to a winter solstice ceremony

The Design and Implementation of AIDA: Ancient Inscription Database and Analytics System

AIDA, the Ancient Inscription Database and Analytic system can be used to translate and analyze ancient Minoan language. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, AIDA provides candidate syllabic values and translations of Minoan words and inscriptions into English. The AIDA system allows the users to change these candidate phonetic assignments to the Linear A, Cretan Hieroglyph and Phaistos symbols. Hence the AIDA system provides for various scholars not only a convenient online resource to browse Minoan inscriptions but also provides an analysis tool to explore various options of phonetic assignments and their implications. Such explorations can aid in the decipherment of Minoan inscriptions. Adviser: Peter Z. Reves

Proposal to encode Old South Arabian Script

This is a proposal to encode the Old South Arabian script in the international character encoding standard Unicode. The script was published in Unicode Standard version 5.2 in October 2009. The script was used from the 8c BCE until 6c CE on the Arabian peninsula, especially in the area of present-day Yemen. It was used to write various southwest Semitic languages of various cultures, such as Minean, Sabaean, Qatabanian, Hadramite, and Himyaritic. Eventually the script was supplanted by the Arabic script

DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep Learning

Twenty-five hundred years ago, the paperwork of the Achaemenid Empire was recorded on clay tablets. In 1933, archaeologists from the University of Chicago's Oriental Institute (OI) found tens of thousands of these tablets and fragments during the excavation of Persepolis. Many of these tablets have been painstakingly photographed and annotated by expert cuneiformists, and now provide a rich dataset consisting of over 5,000 annotated tablet images and 100,000 cuneiform sign bounding boxes. We leverage this dataset to develop DeepScribe, a modular computer vision pipeline capable of localizing cuneiform signs and providing suggestions for the identity of each sign. We investigate the difficulty of learning subtasks relevant to cuneiform tablet transcription on ground-truth data, finding that a RetinaNet object detector can achieve a localization mAP of 0.78 and a ResNet classifier can achieve a top-5 sign classification accuracy of 0.89. The end-to-end pipeline achieves a top-5 classification accuracy of 0.80. As part of the classification module, DeepScribe groups cuneiform signs into morphological clusters. We consider how this automatic clustering approach differs from the organization of standard, printed sign lists and what we may learn from it. These components, trained individually, are sufficient to produce a system that can analyze photos of cuneiform tablets from the Achaemenid period and provide useful transliteration suggestions to researchers. We evaluate the model's end-to-end performance on locating and classifying signs, providing a roadmap to a linguistically-aware transliteration system, then consider the model's potential utility when applied to other periods of cuneiform writing.Comment: Currently under review in the ACM JOCC

An Application of Software Engineering for Reading Linear-B Script

Linear-B script has been studied for sixty years since its decipherment. The laborious efforts of the scholars have revealed many linguistic aspects of the oldest known form of Greek (i.e., Mycenaean/Danaic Greek), thus allowing the study of this Indo-European language and its dynamics for thirty-five centuries. In addition, linguistic phenomena closer to the roots of Indo-European languages can be also studied. Yet, the limited usage of Linear-B script, merely for keeping records, and its incompatibility to the Greek phonotactics causes misinterpretations of various kinds. The study of Linear-B was not supported till recently by interactive software tools that would facilitate both research and training. Especially for Greek speakers, the resources are even more limited. This paper presents the development of an interactive software system for the study, learning and researching of Linear-B by Greek speakers. This software system is also suggested as a model for the interpretation of other archaic languages

Word segmentation for Akkadian cuneiform

We present experiments on word segmentation for Akkadian cuneiform, an ancient writing system and a language used for about 3 millennia in the ancient Near East. To our best knowledge, this is the first study of this kind applied to either the Akkadian language or the cuneiform writing system. As a logosyllabic writing system, cuneiform structurally resembles Eastern Asian writing systems, so, we employ word segmentation algorithms originally developed for Chinese and Japanese. We describe results of rule-based algorithms, dictionary-based algorithms, statistical and machine learning approaches. Our results may indicate possible promising steps in cuneiform word segmentation that can create and improve natural language processing in this area