Stanford EE Computer Systems Colloquium

4:15PM, Wednesday, March 13, 2013
Skilling Auditorium, Stanford Campus

What We Know About the Voynich Manuscript

Kevin Knight and Sravana Reddy
USC and Dartmouth College
About the talk:

The medieval Voynich Manuscript has been called "the most mysterious document in the world". Its pages contain bizarre drawings of strange plants and astrological diagrams, as well as an undeciphered script of 20,000 running words, written in a unique character set. Its origin is also controversial, with many theories abounding. We present current knowledge about the manuscript's text through a series of questions about its linguistic properties.


There is no downloadable version of the slides for this talk available at this time.

Reference Materials for the Voynich Manuscript [provided by EE380 organizers]

Google (or Bing) is your friend if you want to explore what's known about the VoVoynich Manuscript. The Voynich Manuscript is available on the web as high resolution images. There are also serious scholarly works which try to understand the manuscript, it history, and decode it. And, as with many mysterious things, there is a substantial collection of fantasmatic and woowoo interpretations which are unlikely but fascinating. Here is a sampling:

About the speaker:

[Kevin Knight Photo] Kevin Knight is a Senior Research Scientist and Fellow at the Information Sciences Institute of the University of Southern California (USC), and a Research Professor in USC's Computer Science Department. Professor Knight's research interests include natural language processing, machine translation, and decipherment. In 2011, he served as President of the Association for Computational Linguistics and was a member of the team that deciphered a book (the "Copiale cipher") written by an 18th century German secret society.
[Sravana Reddy Photo] Sravana Reddy received her Ph.D. in computer science from the University of Chicago and is now a Neukom Fellow at Dartmouth College. Her work has focused on algorithms to discover linguistic structure from raw data, including learning pronunciations from speech, converting between written and phonetic representations of words, uncovering rhyming and metrical patterns in poetry, and deciphering encoded texts.

Contact information:

Kevin Knight

Sravana Reddy
Computer Science Department
Dartmouth College