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Next-generation transcription of the text


The main page related to text transcription describes the presently available transcriptions systems and files, and a bit of history. In order to fully understand the present page, the reader should be familiar with its contents. The page shows that available transcriptions are based on concepts of several decades ago. They use simple text files which allow very easy parsing by simple tools, which is convenient, but this is not in line with modern representation standards. It was already suggested on that page that a new generation of transcription is due, and a similar feeling was expressed in the page describing my views. The purpose of the present page is to discuss this in more detail.

I would like to address one potential misunderstanding right from the beginning. The existing transcriptions are not "bad". Under the simple assumption that the text of the Voynich MS should be a plain text encrypted using some standard method of the 15th century, it would have been solved easily using even the earliest transcriptions made by Friedman or by Currier. That this did not happen is not the fault of the transcriptions, but of the assumption.

The purpose (in my opinion) of a new transcription effort is to have the best possible data available in a state-of-the-art manner, and capturing much more necessary and useful information than the present transcriptions do. This is independent of the particular approach that one might choose for attacking the text.

From the MS to the transcription files

The source

Our primary source is the physical MS itself. This is, however, not easily accessible. What's more, even if we had some time to study it, we would not be able to do any significant text analysis, since we cannot search the text without leafing through the entire book.

The first derivatives

The first level of abstraction is given by analog pictures of the MS, such as, for example, in the recent photo facsimiles (1). With these, we lose something, namely the interaction with the physical object, and everything that we can only observe from the original. We also gain something, namely ease of access. We can have the book at home and browse it anytime. At the same time, searching the MS is still only possible by leafing through the entire book.

The second level of abstraction is provided by the digital images of the MS. With these, we have a few more advantages, namely:

The next level

The next level of abstraction is given by the electronic text transcriptions, but I won't call this the third level. As will become clear in the course of this page, I would consider this the fifth level of abstraction.

In this lowest abstraction we both lose and gain enormously. What we gain is the fact that we can search the text, both manually and in automated processes, and we can generate statistics, indexes etc. What we lose may be summarised as follows:

  1. We lose a lot of information that may be collected under the header 'layout'. We no longer see the handwriting characteristics, the spacings of the lines, whether characters or words are far apart, etc., etc.
  2. We lose a lot of distinctions in the written characters that may well be relevant. Every transcriber makes many decisions that are irreversible, typically when deciding that two similar-looking character forms were intended to be one and the same, and are therefore transcribed in the same way.

A third problem inherent to transcriptions of the Voynich MS text is a combination of these two points: the uncertain definition of word boundaries or word spaces. The word boundary definitions are based on subjective decisions made by transcribers deriving from the layout of the text.

Some initial considerations

The main transcriptions that are available do not all capture the same information. Those that have been collected in the interlinear file have some useful meta-data. This term means any descriptive data about the text, rather than the transcription itself. These data, among others, identify the location in the MS of each transcribed piece of text, but also additional information. All transcriptions in the interlinear file use the Eva transcription alphabet, but without the special extensions.

The v101 transcription by GC is likely to be the more accurate and consistent one, but this has a less standard location identification and lacks all other meta-data. It is using a different transcription alphabet, and for both historical and practical reasons it is not included in the interlinear file.

This last point is worth a small initial discussion. It will be addressed more fully later. In principle, there is no reason that all transcriptions in the interlinear file should use the same transcription alphabet. It should be possible to identify the alphabet used for each entry in one way or another. That Eva was used for all other ones lies in the fact that Eva was defined such that all existing transcriptions could be converted to Eva without loss of information, and in a reversible manner. For that reason there was no need to maintain the original alphabets, but these alphabets can still be used. The same is not true for v101, and a rendition into Eva might be possible using the extended characters, but this is not certain. It should in principle be possible to define a superset that completely includes both v101 and extended Eva, but it is also not certain that this is the best way forward. This will have to be addressed at some point.

The need to generate a better transcription was also discussed by Nick Pelling at >>this blog post with comments from several contributors. While the name or title "EVA 2.0" is not too appropriate in my opinion, I do think that this was more of a catch phrase rather than a serious proposal.

Making a new transcription is a very significant effort, and it is only worth doing if it really improves upon what is available now. It should preserve the advantages we have now, solve as many of the existing problems and shortcomings as possible, and bring additional advantages.

Exemplifying the problem

To judge the effort in making a new transcription, it would be useful to know how many characters there are in the written text of the MS.

Do we know the answer to this very simple question? No we don't.

After one hundred years of statistical analyses, the answer to this simple question is unknown. What's worse, if four people were asked today to make a count, they would come up with five different answers.

Partly, that is understandable. Which of the transcription files is complete? (Hint: none of them are). Furthermore, there is no agreed definition of the character set. The number depends on this definition. Even if this number cannot be determined yet, it would be important if two people made a count based on the same assumptions, that they end up with the same answer. They should be able to state their assumptions in such a way that someone else could repeat the count and come up with the same answer. Let me therefore insert an intermezzo related to standards and conventions.

Intermezzo: about standards and conventions

Why are they important?

Standards and conventions facilitate collaboration. They allow people to exchange data and results, and for everybody to 'talk the same language'. They allow verification.

This should be completely obvious, but let me just give a small example. Imagine that two people have made their own transcripions of part of the Voynich MS text. Now imagine that someone wanted to compute the entropy values of these two transcriptions. He has a tool to do that. He would need to read and process the two transcriptions, which is easy (and reliable) if both use the same file format, following some convention. If they are not following the same convention, the work is more difficult because the tool has to be modified to read one or the other. As a consequence it is also less reliable since there could be a bug that affects one and not the other. Next, a second person also has a tool to compute entropy. This could be used as a cross-check (verification). This only works well if there is a standard format that all developers of tools can rely on.

Do we have any, and if not, why not?

There are numerous examples of conventions related to the Voynich MS. In the days of Friedman, pages of the Voynich MS were identified with the so-called Petersen page numbers. We still find them, e.g., in Currier's paper (Table A). Nowaways, the standard way to refer to the pages in the MS is using the foliation of the MS. The latter is used in many web resources, and in the transcription files.

Use of the Eva transcription alphabet in discussions about the Voynich MS is an example of a de facto convention. It was not the result of a committee decision that was enforced through some document, but a personal effort of two people (Gabriel Landini and myself) that was considered useful and was generally adopted.

The naming of the various sections in the Voynich MS ("herbal", "biological", "pharmaceutical") is another example that is useful to illustrate some points. Not all people like all of these terms, and as a result, different people use different names for the same thing. While, fortunately, this is irrelevant for the chances of translating the Voynich MS text, it makes communication cumbersome. The point to be made here is that conventions do not need to represent the most accurate way to name or describe things. What matters is that they are usable and that they are generally accepted.

In 'real-life' international collaboration activities, committees or bodies are set up to discuss and agree on standards and conventions, and a majority decision is made. After that, also those who had a different opinion agree to adopt the standard. This is the process that makes collaboration possible. In the world of the Voynich MS, there are no such committees, and everybody is happy to do their own thing. Progress is made by individuals who are not 'talking' but 'doing'. The Eva alphabet, the interlinear transcription file and GC's v101 transcription (2), the Jason Davies Voyager (3) and the text/page browser at (4) are very good examples of this.

Classification of the problems to be resolved

I believe that all improvements that can be made to the present state of Voynich MS transcription can be classified largely into two groups:

  1. How to properly describe the transcribed text in the MS
  2. How to properly store and annotate this information for easy and consistent retrieval

(1) How to describe the text in the MS

The most frequently discussed point in this area is the question what the best transcription alphabet should look like. A large part of the main page is devoted to describing the various historical transcription alphabets, and some of their pros and cons. It is not certain (at least not to me) that there should be one 'best' and commonly agreed transcription alphabet to be used by everybody.

The main problem is the subjectiveness that should be removed, or at least minimised, from the transcription. This is a very complex issue, and in a way it comes down to the definition of the transcription alphabet. This is not the question whether the shape:

should be transcribed as "d" or "8". This is completely irrelevant. The real problem to be solved is how to group similar-looking characters into a single transcribed character.

Looking at this problem in a very abstract manner, one could argue that in principle all characters in the MS are different, since they have been written by hand. This is of course a completely useless way to transcribe the text, but it defines the starting point for the definition of any transcription alphabet:

In principle, every character in the MS could be described by a small graphics file extracted from the digital images. Whether this is a good solution in practice may be doubted, but at least this presents a (hypothetical) additional level of abstraction in between the digital scans and the transcribed text. It may be called the third level of abstration.

Since processing digital images (e.g. in an OCR process) is not yet practically possible, another intermediate level of abstraction could be introduced, namely that of a transcription 'super alphabet'. This would be one that captured all subtle differences between characters, resulting in a very large 'alphabet'. Without claiming that this is the only or even the best solution, I imagine such a super alphabet to be organised into 'character families', i.e. (using Eva just for illustration purposes) a family of all y-like characters, a family of all r-like characters, one of all sh-like characters etc. etc. It could consist of two identifiers for each character: the family identifier and the 'family member' identifier.

Such an alphabet would not be suited for practical statistical analyses, but it would allow researchers to define, use and experiment with their own alphabets. How one would arrive at this alphabet from the digital images is of course not yet clear. At least theoretically, this can be the fourth level of abstraction.

(2) How to store the transcription data

Issues to be resolved here may be developed from the points raised above:

  1. There is a need for a standardised format for representing all past and future transcriptions
  2. Layout information needs to be added, namely the precise location of each text element in the MS, and the handwriting characteristics: character size, writing direction, slant angle (if possible).

Eventually, and ideally, all information should be contained in an on-line database, with query tools to extract what one would need, in well-defined formats. Thus, when I wrote, near the top of this page, that standards like 'TEI' should be supported, I see this as an output from a query to this database.

The definition of such a database is a task that requires preparation. It is not even clear exactly what should be contained in it. Generally speaking, all tools and products that are available now should be able to work on the basis of it, for example any transcription file should be an abstract of it, but also tools like the Jason Davies voyager (see note 3) or the tool known as '' (see note 4). The main thing that is presently not clearly defined is the way to identify the exact location on a page of any text item. The Jason Davies voyager has implemented one method, and '' must also have implemented a solution for this.

In the mean time, the information that should go into this database is collected in several different files of similar, yet not consistent formats. A first step that is needed is to consolidate all this information in a common format based on consistent definitions, and without loss of information. In order to achieve this, I have set up an area at this web site where I am gradually collecting all this information. This includes the definition of an 'Intermediate Voynich Transcription File Format' (IVTFF). It is heavily based on the conventions used by Gabriel Landini and myself in the frame of our transcription efforts in 1998-1999, which also went into the format definition of the interlinear file.

All existing historical transcription files can be represented in this format, meaning that all can be accessed by the same tools. It also allows the ingestion of all transcriptions into a common database using a single tool.

Contents of the IVTFF work area

The main directory has a number of files that will be described below. In addition, there is a subdirectory beta that has files that are not yet in their final version.


See Clemens, 2016, but also Skinner, 2017.
See here.
See here.
See here.


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Copyright René Zandbergen, 2017
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Latest update: 24/06/2017