OCR and Digital Humanities
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The document discusses the transformation of humanities research through digital technologies and optical character recognition (OCR). It describes efforts to extract over 2,000 years of Latin text from digitized books and track linguistic changes over time using machine learning techniques. Computational analysis is helping scholars build dynamic digital editions and study underrepresented languages on a massive scale.
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OCR and Digital Humanities
- 1. OCR and the Transformation of the Humanities Gregory Crane and David Bamman Tufts University Bruce Robertson Mount Allison University John Darlington and Brian Fuchs Imperial College London
- 9. Towards Dynamic Variorum Editions Gregory Crane and David Bamman Tufts University Bruce Robertson Mount Allison University John Darlington and Brian Fuchs Imperial College London
- 11. The Dynamic Variorum as grand challenge
- 14. New Variorum Shakespeare Series
- 15. New Variorum Shakespeare Series
- 16. New Variorum Shakespeare Series “ New” = 140 years old
- 17. New Variorum Shakespeare Series “ New” = 140 years old “ New” vs. 1821 Shakespeare Variorum
- 21. NVS 2011
- 22. NVS 2011
- 23. What was in the 1873 NVS Macbeth?
- 44. Brown’s Intermedia c. 1990
- 46. Shakespeare as an easy case…
- 47. Shakespeare as an easy case…
- 48. Shakespeare as an easy case… c. 500 years of English ….
- 50. Greco-Roman World From Rabat to Kandahar …
- 51. c. 100 CE papyrus from Euclid (c. 300 BCE) http://www.math.ubc.ca/~cass/Euclid/papyrus/papyrus.html
- 52. 800-1000 CE: Greek into Arabic Hunayn Ibn Ishaq (809–873), Arabic version of the Prognosticon from the Hippocratic Corpus http://www.nlm.nih.gov/exhibition/odysseyofknowledge/
- 53. c. 1200-1300: Arabic into Latin Medieval Translation of the Prognosticon from Arabic into Latin
- 54. Return of Greek sources c. 1500 This first edition of Dioscorides' Greek text, printed in Venice in 1499 by Aldo Manuzio (ca. 1447–1515)
- 57. 1. Computational Linguistics David Bamman Tufts University (Carnegie Mellon University) United States
- 60. 2000+ Years of Latin
- 63. 25,886 works catalogued as Latin in the IA, charted by “date.”
- 68. 25,886 works catalogued as Latin in the IA, charted by “date.”
- 69. 7,055 Latin works in the IA, charted by date of composition.
- 72. “ oratio”
- 73. “ lead” vs. “iron”
- 74. Polysemy Words have many senses. Lead Iron (verb) cause to go (verb) to smooth w. an iron be in command (noun) element Fe (noun) position of advantage tool with flat steel base used to smooth clothes chief part in play golf club element Pb graphite in pencil Oratio (noun) Speech Prayer
- 81. 4. WSD Training Source word oratione (oratio) Sense label prayer Training context ad spem pertinent, quae in … dominica continentur
- 84. 5b. WSD time series evaluation
- 85. 5b. WSD time series evaluation
- 87. “ oratio”
- 88. 6. Tracking lexical change: “oratio”
- 90. 2. Digital Classics Bruce Robertson Mount Allison University Canada
- 91. Digitizing and Viewing Difficult Texts: Lessons From Ancient Greek 19th century provides a vast array of editions of Greek text, many still very useful - Yet they could not be accessed digitally What tools and workflows might help us digitize diverse texts such as these? What applications can we create to make the resulting OCR data useful to researchers and students?
- 92. Diversity of 19th Century Fonts and Layout
- 95. Results
- 101. 3. Software Engineering John Darlington Brian Fuchs Imperial College London United Kingdom
- 105. Rapid OCR using MapReduce +a Cloud IaaS
- 116. OCR vote and error prediction methods Courtesy: Federico Boschetti
- 124. Conclusions
- 128. Plato ’ s Republic and the Guardians The Islamic Republic of Iran and the Guardianship of Islamic Jurists
- 129. Sometimes Greek philosophy does have an impact.. Plato ’ s Republic and the Guardians The Islamic Republic of Iran and the Guardianship of Islamic Jurists
- 132. Students of Greek and Latin
- 133. Students of Greek and Latin
- 134. Students of Greek and Latin
- 135. How do we work together?
- 139. Student Researchers Tufts Holy Cross
- 140. Student Researchers Tufts Furman Holy Cross
- 141. Student Researchers Tufts Furman Holy Cross Houston
- 142. Student Researchers Tufts Furman Holy Cross Mount Allison Houston
- 145. We can (if we choose) transform our ability to advance the intellectual life of society
- 146. Thank you!
Notes de l'éditeur
- Checked Shakespeare Quarterly 61.1 Spring 2011 – of 100 randomly selected footnotes with secondary source citations, 99 cited English. 1 cited french. A handful cited Greek and Latin sources but in each case cited English translations. There were 4 articles and a review essay
- So “a” solution that we’re presenting here is the idea of transferring markup from a richly annotated source text to a plain-text translation (that can be nothing more than perhaps badly OCR’d words). So at a high level, this is done in two steps: an alignment step and a projection step. First we align the source document with the target document in a cascading process and when we have this alignment completed, we then project the XML tags across documents in a way that exploits the similarity in the linguistic structure between that text pair.
- 1. ocr outputs are aligned by a multiple sequence alignment dynamic algorithm (similar to BLAST, Clustal, etc., used in bioinformatics for DNA alignment) -- 2. the bayesian classifier determines, character by character, which character is more reliable, taking into account the probability that a particular engine provides that good character, when the other engines provides their bad characters (ex.: e1=R e2=P e3=B <-- R is the most probable on e1 output, when e2 provides P and e3 provides B) This is the reason that I don't use a 2-to-1 method but a bayesian classifier: many times we have THREE DIFFERENT THINGS! 3. when we have wrong sequences, the spellchecker provides suggestions. It is accepted only the (first) suggestion that is a sequence of characters appearing at least on one of the three engines (ex.: e1=zoure e2=poqse e3=hoxxe<--house [h-o-u-s-e are provided, in the correct position, at least by one engine:h in e3, o in everyone, u in e1, etc.)]]