Difference between revisions of "Cracking the Voynich code 2022"

From Derek
Jump to: navigation, search
(→‎Deliverables [WIP])
(→‎Link to Box with Deliverables)
Line 78: Line 78:
  
 
===Link to Box with Deliverables ===
 
===Link to Box with Deliverables ===
−
https://universityofadelaide.box.com/s/e7flatpfnuh2ozx3rrsmk6o4rwv5nt8h
+
https://universityofadelaide.box.com/s/phopkpou146qulsxdvkn35t7mvxx90p2
  
 
== Weekly progress and code [WIP]==
 
== Weekly progress and code [WIP]==

Revision as of 18:11, 22 November 2022

Supervisors

Masters students

Project guidelines

General project description

Building on the work of previous honours students, this project involves contributing to the growing body of knowledge aimed at deciphering the Voynich Manuscript. This 15th century text is written in an unknown script and has been an area of interest for cryptographic researchers for centuries.

The specific goal of this project is to categorize characters in the Voynich script into alphabetical and non alphabetical groups. This outcome would be an invaluable piece of knowledge for future researchers to build on towards the goal of eventually deciphering the mysterious text.

Useful notes

  • Download the digital Voynich from here.
  • The UN Declaration of Human Rights is translated into every language in the world and in principle you can compare the Voynich to all the existing languages for statistical proximity. Electronic access is here.

Specific tasks [WIP]

Phase 1: Literature Review and Formatter

Reilly

  • Reading work of past students
  • Design and development of text formatter

Greg

  • Reading of existing Voynich literature


Phase 2: Text Summary & Frequency Analysis

Reilly

Text Characterization

  • Distinct Sections
  • Word count
  • Longest and shortest words
  • Other text features of note

Greg

  • Frequency of each word
  • Longest and shortest words
  • Frequency profiles of each character to compare anagram results with other languages more accurately
  • Frequency profile of characters occurring at start and ends of words to verify findings of previous students
  • Other frequency details of note

Phase 3: Anagram properties of words & Hidden Markov Models

Reilly

  • Develop a program that anagrams words and finds instances of its anagrams in the rest of the text
  • Test program on English texts
  • Test program on texts of other languages
  • Run program on Voynich Manuscript
  • Check whether as in English, words in the manuscript can only anagram into words and numbers into other numbers
  • Research whether this behavior holds for other languages
  • Look at frequency of successful anagrams being acquired and compare to other languages, potential insights into words vs numbers
  • May give insight into characters that frequently appear in words, potential vowel-consonant adjacent writing system

Greg

  • Apply hidden Markov models in an attempt to categorise characters


Phase 4: Optical Character Recognition & Other Ideas

Reilly

  • Further research and additional approaches

Greg

  • Development of OCR in an attempt to produce a new transcript through modern techniques

Deliverables [WIP]

Semester A

  • Project Management Plan: 18/March/2022
  • Technical Resources Quiz: 18/March/2022
  • Group Evaluation #1: 08/April/2022
  • Intellectual Property Form: 08/April/2022

Semester B

Link to Box with Deliverables

https://universityofadelaide.box.com/s/phopkpou146qulsxdvkn35t7mvxx90p2

Weekly progress and code [WIP]

Weekly progress:

Code:

Approach and methodology [WIP]

We expect you to take a structured approach to both the validation and the writing of the software. You should carefully design the big-picture high-level view of the software modules, and the relationships and interfaces between them. Think also about the data transformations needed.

Expectations

  • We don't really expect you to crack the Voynich, though that would be cool if you do and you'll become very famous overnight.
  • To get good marks we expect you to show a logical approach to decisively eliminating some languages and authors, and finding some hints about the statistical nature of the words.
  • In your conclusion, you need to come up with a short list of possible hypotheses and a list of things you can definitely eliminate.
  • We expect you to critically look at the conclusions of the previous work and highlight to what extent your conclusions agree and where you disagree.
  • It is important to regularly see your main supervisors. Don't let more than 2 week go by without them seeing your face briefly.
  • You should be making at least one formal progress meeting with supervisors per month. It does not strictly have to be exactly a month, but roughly each month you should be in a position to show some progress and have some problems and difficulties to discuss. On the other hand the meetings can be very frequent in periods when you have a lot of activity and progress to show.
  • The onus is on you to drive the meetings, make the appointments, and set them up.

Relationship to possible career path

Whilst the project is fascinating as you'll learn about a specific high-profile mystery—and we do want you to have a lot of fun with it—the project does have a hard-core serious engineering side. It will familiarize you with techniques in information theory, probability, statistics, encryption, decryption, signal classification, and datamining. It will also improve your software skills. The new software tools you develop may lead to new IP in the areas of datamining, automatic text language identification, and also make you rich/famous. The types of jobs out there where these skills are useful are in computer security, comms, digital forensics, internet search companies, and language processing software companies. The types of industries that will need you are: the software industry, e-finance industry, e-security, IT industry, Google, telecoms industry, ASIO, ASIS, defence industry (e.g. DSD), etc. So go ahead and have fun with this, but keep your eye on the bigger engineering picture and try to build up an appreciation of why these techniques are useful to our industry. Now go crack the Voynich...this message will self-destruct in five seconds :-)

See also

Useful papers we wrote

[1] M. Ebrahimpour, T. J. Putniņš, M. J. Berryman, A. Allison, B. W.-H.-Ng, and D. Abbott, "Automated authorship attribution using advanced signal classification techniques," PLoS ONE, Vol. 8, No. 2, Art. No. e54998, 2013, http://dx.doi.org/10.1371/journal.pone.0054998

[2] M. J. Berryman, A. Allison, and D. Abbott, "Statistical techniques for text classification based on word recurrence intervals," Fluctuation and Noise Letters, Vol. 3, No. 1, pp. L1–L12, 2003.

References and useful resources

If you find any useful external links, list them here:

Back

Retrieved from "https://www1.eleceng.adelaide.edu.au/personal/dabbott/wiki/index.php?title=Cracking_the_Voynich_code_2022&oldid=23142"