Image and interpretation using artificial intelligence to read ancient Roman texts

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes a system that assists expert papyrologists in the interpretation of the Vindolanda writing tablets. A model-based approach is taken that relies on models of the written form of characters, and statistical modelling of language, to produce plausible interpretations of the documents. Fusion of the contributions from the language, character, and image feature models is achieved by utilizing the GRAVA agent architecture that uses Minimum Description Length as the basis for information fusion across semantic levels. A system is developed that reads in image data and outputs plausible interpretations of the Vindolanda tablets

Agendas for Digital Palaeography in an Archaeological Context: Egypt 1800 BC

Handwriting raises issues alive in archaeological debates, philosophical and historical. In turn, by their extreme fragmentariness, the earliest archaeological manuscripts could generate usefully different questions for the field of palaeography. Here, digitisation offers new common ground for the separate disciplines in the study of the past. For current archaeological discussions of structure and agency, manuscripts pose the act of writing, between social and individual. For debates over literacy and power in part- literate societies, an archaeological hoard of manuscript fragments offers opportunities to assess our chances of knowing, for one time and place, how many writings and writers. The largest earliest group of writing on papyrus-paper comprises several thousand small fragments from Lahun in Egypt (about 1850–1750 BC). Traditional methods of recording similarity and difference across the collection can now be accelerated to a point of qualitative change, by applying image-matching software. This paper considers the potential of computer-aided palaeography for generating new research agendas

Combining diverse systems for handwritten text line recognition

In this paper, we present a recognition system for on-line handwritten texts acquired from a whiteboard. The system is based on the combination of several individual classifiers of diverse nature. Recognizers based on different architectures (hidden Markov models and bidirectional long short-term memory networks) and on different sets of features (extracted from on-line and off-line data) are used in the combination. In order to increase the diversity of the underlying classifiers and fully exploit the current state-of-the-art in cursive handwriting recognition, commercial recognition systems have been included in the combined system, leading to a final word level accuracy of 86.16%. This value is significantly higher than the performance of the best individual classifier (81.26%

The influence of humanism on the handwriting of Michelangelo Buonarroti

The handwriting of Michelangelo Buonarroti underwent a distinct and permanent change between 1497 and 1502. The handwriting of his early letters of 1496 and 1497 is merchantescha, the gothic cursive mercantile script which he would have learned at school. The later handwriting is cancellarescha, a humanistic cursive. It is present in letters, contracts, memoranda, records of accounts, and in annotations on drawings. Both scripts as written by Michelangelo are analyzed paleographically and are compared to examples from instructional writing books of the period. The impossibility of evolution from one script to the other is demonstrated through analysis of the scripts and a review of the history of book hands. The alteration must therefore have been the result of a conscious decision by the artist to modify his handwriting. The decision was made as a result of the influence of Humanism and, to a lesser extent, Neoplatonism

History’s Absent Hand: Lessons in Modes of (Textual) Production from Gaétan Soucy’s The Little Girl Who Was Too Fond of Matches

Following its initial publication in 1998, Gaétan Soucy’s third novel, La Petite fille qui aimait trop les allumettes, has been translated into several languages, including Sheila Fischman’s critically acclaimed English version, The Little Girl Who Was Too Fond of Matches (2000). While Soucy’s fictional autobiography is frequently read as a contemporary Gothic fairy tale and/or trauma memoir, this essay explores the text’s treatment of modes of material production as a lesson in re-visioning history as a process of “non-synchronous simultaneity” or ungleichzeitigkeit (in Ernst Bloch’s terms) that is ultimately based on an “absent cause” (Althusser, Jameson). Insofar as questions of material production in Soucy’s narrative include the central question of textual production, the essay considers how The Little Girl Who Was Too Fond of Matches anticipates problems of authenticity, authority, ownership, and literary estate that are necessarily raised by the novel’s own re-production as a text in translation. Finally, the essay examines the shift or translation from the technology of handwriting to that of print at the heart of Soucy’s complex, poetic novel as a potential parable for (in Marshall McLuhan’s term) a “post-literate” 21st century, one pointing to a present in which what may be disappearing -- or becoming history -- includes precisely the “old” technology of the cursive hand itself. 

Handwriting recognition by using deep learning to extract meaningful features

[EN] Recent improvements in deep learning techniques show that deep models can extract more meaningful data directly from raw signals than conventional parametrization techniques, making it possible to avoid specific feature extraction in the area of pattern recognition, especially for Computer Vision or Speech tasks. In this work, we directly use raw text line images by feeding them to Convolutional Neural Networks and deep Multilayer Perceptrons for feature extraction in a Handwriting Recognition system. The proposed recognition system, based on Hidden Markov Models that are hybridized with Neural Networks, has been tested with the IAM Database, achieving a considerable improvement.Work partially supported by the Spanish MINECO and FEDER founds under project TIN2017-85854-C4-2-R.Pastor Pellicer, J.; Castro-Bleda, MJ.; España Boquera, S.; Zamora-Martinez, FJ. (2019). Handwriting recognition by using deep learning to extract meaningful features. 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Easily Read, Easily Forgotten: Reassessing the Effects of Visual Difficulties and Multi-Modality in Educational Text Design

The graphic design of a book affects the way the reader receives and processes information. However, design is often focused on aesthetic principles and traditional wisdom, not taking into account how design aspects affect cognitive processes and educational outcomes. This thesis examines the efficacy of page design elements on educational outcomes, specifically disfluent fonts, handwritten fonts and multi-modal design. The traditional wisdom of typography has maintained that the faster the human eye can read a text, the more suited it is for reading materials. However, recent research suggests that disfluent, or difficult-to-read fonts result in significantly improved reading comprehension and retention (Chih-Ming Chen & Yu-Ju Lin 553; Diemand-Yauman, et al. 114; Faber, et al. 914; French, M. M. J., et al. 301; Geller, Jason, et al.1109; Halin, et al. 31; Oppenheimer D.M & Frank M.D. 1178). This body of research suggests that certain visual disfluencies enhance educational outcomes, improving retention and comprehension by encouraging the reader to mentally process material in a slower and deeper way. What if texts that are easily read are easily forgotten? Medieval manuscript design encouraged a reading culture nurtured by deep, contemplative and slow reading methods, enhanced by semiotic images, text and design. The modern book designer, inspired by medieval manuscripts, and their modern incarnation, the graphic novel, can enhance educational outcomes through design that elicits a deep cognitive processing. The aim of this thesis is to present evidence that this inspiration combined with difficult-to-read fonts and multi-modal design can enhance educational outcomes, specifically in the American high school literature classroom