Special Topics: Transliteration of the text

The main page related to transliteration is here. The present page has the following topics:

• Next-generation transliteration of the text
• Text that has not (yet) been transliterated
• New transliteration file format
• Consolidating the IVTFF format
• Transliteration file processing tools:
•     Voynich transliteration tool
•     Bi-directional translation/substitution tool

Next-generation transliteration of the text

Introduction

The main page related to text transliteration describes the presently available transliteration systems and files, and a bit of history. In order to fully understand the following discussion, the reader should be familiar with its contents. The 'main page' shows that available transliterations 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 not in line with modern representation standards. It was already suggested on that page that a new generation of transliteration is due, and a similar feeling was expressed in the page describing my views. In the following this is discussed in more detail.

I should first address one potential misunderstanding: the existing transliterations 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 transliterations made by Friedman or by Currier. That this did not happen is not the fault of the transliterations, but of the assumption.

Now even though the existing tansliterations are not 'bad', there is certainly room for significant improvement.

The purpose (in my opinion) of any new transliteration 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 transliteration files do. This is independent of the approach selected for analysing the text.

The source of all transliterations

Our primary source is the physical MS itself. This is, however, not readily 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. We therefore need to use derivatives of the original to work with.

The first derivative

The first level of abstraction is given by pictures of the MS. These may be analog pictures 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.

Even more useful are digital images of the MS, which we may call the first derivative. With these digital images, we have a few more advantages, namely:

The 'final' derivative

Our target level of abstraction consists of the electronic text transliterations, but I won't call this the second level. As will become clear in the course of this page, I would consider this the fourth 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:

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

Some initial considerations

The main transliterations 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 transliteration itself. These data, among others, identify the location in the MS of each transliterated piece of text, but also additional information. All transliterations in the interlinear file use the Eva transliteration alphabet, but in the 'Basic Eva' form without the special, important extensions.

The v101 transliteration 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 transliteration alphabet, and for both historical and practical reasons it has not been 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 transliterations in the interlinear file should use the same transliteration 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 transliterations 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 even a rendition into Eva using the extended characters is not possible without loss of information.

The need to generate a better transliteration 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 entirely appropriate in my opinion, I suppose that this was more of a catch phrase rather than a serious proposal.)

Making a new transliteration 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 transliteration, 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 transliteration files is complete? (Hint: none of them are). Furthermore, there is no agreed definition of the character set. The number of characters depends on this definition. Even if this number cannot be determined yet, it would be important that, if two people made a count based on the same assumptions, 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 (users 1 and 2) have made their own transliterations of part of the Voynich MS text. Now imagine that someone (user 3) wanted to compute the entropy values of these two transliterations. He has a tool to do that. He would need to read and process the two transliterations, 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 of user 3 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 transliteration files.

Use of the Eva transliteration 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 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 transliteration file and GC's v101 transliteration (2), the Jason Davies Voyager (3) and the text/page browser at voynichese.com (4) are excellent examples of this.

Classification of the problems to be solved

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

(1) How to describe the text in the MS

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

The main problem is the subjectiveness that should be removed, or at least reduced, from the transliteration. This is a very complex issue, and in a way it comes down to the definition of the transliteration 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 transliterated 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 would of course be a completely useless way to transliterate the text, but it defines the starting point for the definition of any transliteration 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 seriously doubted, but at least this presents a new, even if perhaps not very practical, level of abstraction in between the digital scans and the transliterated text. It may be called the second level of abstraction.

Since automated transliteration from digital images (e.g. in an OCR process) is not yet practically possible for the Voynich MS and other handwritten documents (5), another intermediate level of abstraction could be introduced, namely that of a transliteration 'super alphabet'. This would be one that captured all subtle differences between characters, resulting in a very large 'alphabet'. How should this be defined or organised?

Without claiming that this is the only or even the best solution, I imagine such a super alphabet to be organised into 'character families'. This may be explained using Eva just for illustration purposes: there could be 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 not yet clear. At least theoretically, this rendition of the text using a 'super alphabet' can be the third level of abstraction.

While a definitive Super Translitation Alphabet (STA) would be defined after a renewed transliteration effort, undoubtedly including numerous new characters, it is already possible to define such an alphabet as a superset of all existing transliteration alphabets. This effort has been done, and after an iterative procedure, I have defined such an alphabet, which is referred to as "STA-1" or just simply "STA". It was achieved after an iterative process.

This effort was first presented at the 2022 online Voynich MS conference (6), where the alphabet was still preliminary, while its final state is described in more detail on a dedicated page at this site.

(2) How to store the transliteration data

The issues related to data storage / formats that should be resolved may be developed from the points raised above:

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 should be decided exactly what should be contained in it. Once such a database is defined, all tools and products that are available at present should be able to work with it. For example: any transliteration file should be an extract of it, but also tools like the Jason Davies voyager (see note 3) or the tool known as 'voynichese.com' (see note 4) could be based on this database. One important aspect of this is that there is presently no standard for identifying the exact location on a page of any text item. The Jason Davies voyager has implemented one method, and 'voynichese.com' has implemented another. The data from the latter are available at that site in the form of XML files, which is an extremely valuable resource that has hardly been used outside this web site.

Summary

The following table summarises the abstraction levels and their relative usefulness that were introduced above.

The following bullet list includes my suggestions on what could be done on the short and intermediate term to arrive at a better transliteration database:

• In the above table, processed MS scans were introduced. One can define several types of processed images, but the main purpose here is to facilitate OCR processing. This means that all drawing elements and other disturbing items should be removed, while keeping the original image sizes. The generation of these images is by itself an interesting area of research and application of machine learning including, e.g. neural networks. I suspect that implementations of this already exist.
• A coordinate system to identify locations in the MS needs to be defined. My proposed method is to base it on the original scans available via the Beinecke digital library. I proposed that the location should be X in pixels (left to right) and Y in pixels (top to bottom), which is also the method used at "voynichese.com". For each character an 'anchor point' could be defined, which I would propose to be on the writing baseline, in the middle of the character. A practical problem is that not all text is visible on these scans.
• A 'super alphabet' should be defined. This could be done initially as a mainly manual task, by creating a common superset of Extended Eva and v101 (which has been done - see above). As a next step, the locations of all characters in the MS could be searched from the processed images automatically, by an OCR-type process aided by existing transliterations.
• A database layout needs to be defined. The output of the previous step has to be imported into it. Additional metadata need to be included in it.
• Using some combination of manual and automated effort, the transcription database and the 'super alphabet' can be improved iteratively.
• An official location for storage of all data should be identified. At the time of writing, the DECODE database in Uppsala could be an appropriate location.
• Tools should be developed to work with the database, e.g. to define proprietary transliteration alphabets, to allow an intelligent search for text, and to extract text segments into standard file formats.

Of all bullet points above, only one still appears obscure and may require considerable further thought, and is clearly a longer-term objective. This is the point related to iterative improvement of the database and 'super alphabet'.

It should be noted that the above database is not only useful for text analysis, but also for some aspects of handwriting analysis, e.g. text size, slant angle, line distance, maintenance of margins, etc. For these aspects, no numerical data is presently available.

At the start of the year 2023 I embarked on a medium-to-long term activity to implement all of the above. I refer to this activity as "integrated text and image processing of the Voynich MS", and documentation of this activity will gradually appear, and be referred to here and at "academia.edu".

This activity is making use of what I would like to call: 'assisted OCR'. This is a two-step OCR process that makes use of a priori information of the text to be recognised. This a priori information is contained in a so-called 'reference transliteration', of which a prototype is already available and presented at the main page (see table).

Step 1 of this process consists in finding the precise location of each character in the reference transliteration, and improving this transliteration in the process, by correcting for missing or superfluous characters.

Once this has been achieved, step 2 of the process consists in better identifying the characters at the established locations. While the STA alphabet is at the basis of this activity, for the OCR it is more convenient to use a stroke-based transliteration. For this purpose, yet another alpabet has been defined (still in prototype form) which I have called "aaa" (analytical alignment alphabet). Its sole purpose is to facilitate alignment of different transliterations, and alignment of a transliteration to the MS images. It will be documented here as soon as there is a stable definition.

Text that has not (yet) been transliterated

Introduction

Several more-or-less complete transliterations of the Voynich MS text have been made, and are presented in a table on the main page. However, some text in the MS is missing in all of them. It is either not represented at all, or represented by the sequence "???", meaning: an unknown number of illegible characters.

Here, we are not concerned with text on pages that have been lost (such as e.g. folio 12 or folio 74), but with text that is on the extant folios.

We are also not concerned with text that we can see clearly, but we can't figure out which characters are there. An example of that is part of the text around the sun face at the bottom of folio f68r2, see lower left quadrant in the following figure. Here, we can't even decide which part of the text is in the unknown script, and which part is 'cleartext'.

What we are concerned with here is text that we know is there or should be there, but it hasn't been transliterated (yet) because we can't see it properly. The text may not have been photographed, for example, or it may be behind layers of paint, or it may have been damaged.

To assess this, it is useful to first present the list of sources from which the transliterations may be made:

The 'best' source to start from is "C", the set of digital scans at the Beinecke digital library, because it is easily acessible and nearly complete. The list of badly readable parts may be made starting from this source, and is presented below. In the table, "Locus" refers to the identification of the item in the IVTFF transliteration. "Problem description" is usually based on what we see in the Beinecke 2014 scans (source "C").

This is work that is still very much in progress....

New transliteration file format

Introduction

For the analysis of the various Voynich MS text transliterations, it is highly desirable that these transliterations are contained in files with a well-defined (standardised) format. Such files should be 'annotated', meaning that they include so-called metadata, which is not the text itself, but information about the text. This metadata should indicate, for example, for each particular piece of text on which folio or page it is located, and where it is on the page. In earlier days, this location information was called the "locus", a term that I shall continue to use. Additional relevant information about the pages or the text may be included. Analysis software should be able to either interpret this information or to ignore it.

In the earliest days of the internet, when the transliteration by Currier was being extended, a format was agreed for this new file. This format was extended in the course of the EVMT transliteration by Gabriel Landini and myself. It was further modified by Jorge Stolfi, and used in this final version in the main resource: the Stolfi-Landini interlinear file.

Unfortunately, the differences between the above three formats are quite significant, and the v101 transliteration file uses yet another, completely different representation. It is not particularly useful to describe any of these formats in more detail.

To achieve a new common format, the following steps have been undertaken in 2017:

Inventory of available transliteration files in 2017

Three nearly complete transliterations of the text exist, but how complete are they in reality? To answer this question, I have compared all three with each other, and with the digital images of the MS. This showed first of all that there are some inconsistencies in counting the different loci. The following table presents the total counts:

It appeared that none of the transliterations was complete, and there are even some loci that are not included in any of them. Furthermore, there are several inconsistencies between the definition of individual loci in these files. The much lower number in the GC file is due to the fact that GC grouped many individual labels together under single loci, which he gave long descriptive names. The much smaller difference between the LZ and LSI files is related among others to the different grouping of multi-word labels. These differences are addressed in more detail in the following, in order to arrive at a common definition, where possible based on a majority, while also taking into account the older transliteration efforts initiated by Friedman and Currier.

Locus adjustments

Following are the major inconsistencies between the definition of individual loci in the main transliteration files, and the way these can be resolved.

Locus types

In the oldest transliteration files (FSG, C-D), loci were simply numbered incrementally from 1, but these did not include transliterations of special items like labels, circular text etc. In the frame of the EVMT activity, where these were all included, labels were prefixed by L, circular and radial text by C and R, individual words that were not near a drawing element by S and 'blocked' text (consecutive lines that were not part of the standard paragraphs) by B.

This usage was extended by Stolfi in the LSI file, but unfortunately in quite an inconsistent manner, due to the fact that there were various different people doing the transliteration. Standard paragraph text was prefixed by P, but sometimes also P1, P2 etc if the different paragraphs could be counted easily. Thus, the first line could be P.1, P1.1 or P.1.1 depending on the page. Other codes were introduced, covering almost half the alphabet, and also some lower-case letters. L sometimes meant "label" and sometimes "left". This issue still affects online tools that extract text from the interlinear file.

A new convention, more similar to EVMT, has therefore been introduced in 2017, where the locus type is characterised by one of four main types (upper case characters), and a longer list of sub-types (second character: lower-case character or number), as follows:

The inventory

Based on the above rules, the total number of loci in the MS could be established. After adjusting the loci in each of the files according to the rules listed above, the completeness of each transliteration file could be established, in terms of the number of loci covered. The analysis showed that the "LZ" transliteration, which benefited strongly from the work of Theodore Petersen, was most complete. It lacked only:

• The few characters in script in the right margin of f1r (3 are visible)
• The short words under the paint of a leaf on f2r (missing in all existing files).
• An entry in the left margin of f11v (also missing in all existing files).
• The words in Voynichese script that are included in the top margin of f17r, visible only under UV light (equally missing in all existing transliteration files).
• The two Voynichese words on f116v, which were only included in "LSI".

I decided to extract my own transliteration from the LZ combined effort, and this will be called ZL in the following. The few loci that were missing in LZ were added to this file. I am continually updating it, and it is presently at issue 2a. The counts in the following table reflect the status of the files after a considerable verification exercise in 2019-2020.

Format adjustments

The new format is based on minimal adjustments to the conventions used by Gabriel Landini and myself in the frame of our transliteration efforts in 1998-1999, which also went into the format definition of the interlinear file, where they can still be found (which is why these details are still presented here). There were a number of issues to be resolved, mainly related to the character set of the v101 alphabet, which was shown here. Problems existed with the following characters:

New file format

The result of this exercise was the definition of a new format, which I have called IVTFF (Intermediate Voynich Transliteration File Format). The complete format description (version 2.0 of February 2023) may be found in this PDF document. (Note that the earlier version 1.7 may still be found on the legacy page).

The table below summarises the most important conventions used for this format.

For additional conventions and details, see the format definition.

There are three types of locus indicators:

Inventory of the transliterated text

All loci have been classified into different types, which are identified by two characters. Following is the distribution of the loci over these types, for the entire MS (7).

The following table summarises the coverage of these loci in each of the five main transliteration files.

Page variables

An additional feature of the IVTFF format is the use of so-called page variables. Further above, the page start locus type was introduced. On these lines, no transliterated text is allowed, but there can be a dedicated comment setting page variables, which may look like this:

This dedicated comment sets a number of variables ($Q, $P etc.) to certain values for the whole page. This allows software to select or de-select pages based on these settings. An example of this is the transliteration file (pre-)processing tool "ivtt" which is introduced further below, and which has this capability built in. The meaning of the most important page variables is included in the table below. A complete list with all possible values is given in the IVTFF format definition.

Consolidating the IVTFF format

The IVTFF format described above had been at version 1.7 since April 2020. This format left some freedom in certain areas, and as a consequence it had not been followed strictly in most of the files. For a fully consistent automated processing, it has become desirable to resolve these minor issues, which was achieved by the equally minor update to version 2.0.

The main issue was related to the use of the code <-> to indicate that the text is interrupted by a drawing element, most commonly part of a plant drawing. This code replaces the minus sign that was already used for this purpose in transliteration files in the 1990's. When this occurs, there is usually a period (indicating a word space) directly before or after the <-> , but not always. To resolve this, the new rule is that the <-> code implies a word space.

Secondly, the code <~> had been introduced to indicate a bad vertical alignment between consecutive words. This has only ever been used in the ZL file, and at the location of a drawing intrusion of the text. This has usually been represented as <-><~> . The new rule is that the <~> code implies a <-> , and thereby a word space.

Furthermore, especially older files would have periods (word spaces) at the beginning or end of a line, and newer files had <-> codes at the beginning or end of a line, all of which are not meaningful. The format consolidation therefore introduces the following rules:

• There are four possible representations of a word space:
  - A comma to denote an uncertain word space
  - A period (full stop) to denote a certain word space
  - The code <-> to denote a text interruption by a drawing element, which implies a certain word space
  - The code <~> to denote a text interruption by a drawing element, which implies a certain word space. In this case, the text to the left and right are not well aligned vertically
• It is not allowed to have two or more of these symbols in sequence. Only one of them shall appear between adjacent words.
• None of these symbols shall appear at the start of a line or at the end of a line

A further important change (affecting only the ZL file) is that it is now obligatory for all uncertain readings to include a colon, i.e. [ao] is no longer allowed, and this shall be written as [a:o].

There are other very minor rule changes, which are all included in the format definition, for which see IVTFF format 2.0 definition.

The change to the meaning of the <-> and <~> dedicated comments means that the way they are processed by ivtt could be improved as well. In particular the option -p related to these comments should now allow the following:

• -p1 to convert <-> and <~> to a normal (full) space and leave paragraph start and end codes <%> and <$> unchanged.
• -p2 to convert <-> and <~> to a normal (full) space and delete paragraph start and end codes <%> and <$> .
• -p3 to delete all four codes: <-> , <~> , <%> and <$> .

For this purpose, ivtt version 2.0 has been created, which has a few additional minor changes, mainly an additional option (-m3) to run in diagnostics mode only. In this case, no output file is generated, but only warning or error messages are generated when applicable.

Note that the previous ivtt version (1.3) can perfectly process files with IVTFF format 2.0, and ivtt version 2.0 can perfectly process older files, but the options to handle the dedicated comments described above are less well suited for the purpose.

All transliteration files using IVTFF format 2.0 are accessible through tables here and here.

Transliteration File processing tools

(See also the descriptions in the ReadMe file.)

ivtt: (Intermediate) Voynich Transliteration Tool

In the course of the transliteration collaboration with Gabriel Landini, I developed a tool to pre-process transliteration files. At the time, I made very extensive use of this tool, among others to do the analyses presented here, here and here, but since our transliteration was never published, this tool was never used by anyone else. It has been converted in order to process files in the IVTFF format.

The new version of this tool has been named (prosaically) IVTT (Intermediate Voynich Transliteration Tool). Its user manual is provided here, and the latest source code in C is provided here. Users also need to be familiar with the IVTFF format definition.

Please note that the latest version of the source code is 2.1, dated 24 August 2024, which resolves a few bugs in version 2.0. Versions 2.0 and higher process IVTFF files in the format version 2.0. The manuals listed above are also valid for ivtt software version 2.1.

The earlier software version 1.3, which processed IVTFF file using format version 1.7, can still be retrieved through the legacy page.

Rather than explaining the usefulness of this tool by duplicating information from its user guide and the IVTFF format definition, I prefer to show this by giving a few simple examples.

Examples

One of many uses of the tool is to select specific parts of a transliteration file. For example, the command:

ivtt +QO +@Lc ZL.txt

Can be used to extract all container labels in quire 15 from the ZL transliteration file. The result is:

<f88r>         <! $I=P $Q=O $P=C $L=A $H=4>                                     
<f88r.1,@Lc>     otorchety
<f88r.12,@Lc>    otaldy
<f88r.23,@Lc>    ofyskydal
<f88v>         <! $I=P $Q=O $P=D $L=A $H=4>                                     
<f88v.1,@Lc>     okalyd
<f88v.11,@Lc>    otoram
<f88v.27,@Lc>    daramdal
<f89r1>        <! $I=P $Q=O $P=F $L=A>                                          
<f89r1.1,@Lc>    okchshy
<f89r1.11,@Lc>   ykyd
<f89r1.24,@Lc>   ykocfhy
<f89r2>        <! $I=P $Q=O $P=G $L=A>                                          
<f89r2.1,@Lc>    odory
<f89r2.9,@Lc>    otold[:y]
<f89r2.16,@Lc>   korainy
<f89r2.29,@Lc>   okain
<f89r2.30,+Lc>   yorainopaloiiry
<f89v1>        <! $I=P $Q=O $P=J $L=A>                                          
<f89v1.1,@Lc>    okoraldy
<f89v1.21,@Lc>   <!container>koeeorain

To remove the 'dressing' and leave only the transliterated text, the command issued above can be changed (for example) as follows:

ivtt -f1 -c5 +QO +@Lc ZL.txt

The same can be done reading the GC file:

ivtt -f1 -c5 +QO +@Lc GC.txt

or for Takeshi's transliteration as included in the LSI file:

ivtt -f1 -c5 +QO +@Lc -tH LSI.txt

The results of the three commands are shown below, next to each other:

otorchety
otaldy
ofyskydal
okalyd
otoram
daramdal
okchshy
ykyd
ykocfhy
odory
otold[:y]
korainy
okain
yorain
choeesy
otory
opaloiiry
okoraldy
koeeorain

okoy1ck9
okae89
of9sh98ae
ohAe98
okoyap
8ayap7ae
oh159
9h98
9hoF9
o8oy9
okoe89
hoyan,9
ohan
9oyan
1oCs9
okay9
ogaeoZ9
ohayae79
hoCoy,an

otorchety 
otaldy 
ofyskydal 
okolyd 
otoram 
daramdal 
okchshy 
ykyd 
ykocfhy 
odory 
otoldy 
korain.y 
okain
yorain 
choeesy 
okory 
opaloiiry 
okoraldy 
koeeorain 

As another example, one may quickly see that centred lines in normal paragraph text occur equally in pages written in Currier language A and in Currier language B:

ivtt -x7 +@Pc +LA ZL.txt
>>
ytchas oraiin chkor
dainod ychealod
ychekch y kchaiin
saiinchy daldalol
sam chorly
otchodeey
dorain ihar
okar sheey shekealy
teol cheol otchey ???cheor cheol ctheol cholaiin chol qkar

and

ivtt -x7 +@Pc +LB ZL.txt
>>
oteor aiicthy
oteol cholkal qokal dar ykdy
pchedy chetar ofair arody
yteched ar olkey okeoam
s ar chedar olpchdy otol otchedy
dar oleey ol yy
otar chdy dytchdy
otoiir chedaiin otair otaly

bitrans: Bi-directional Translation / Substitution Tool

Bitrans is a tool that can perform text substitutions to any plain text file. In addition, it provides specific support for files in the IVTFF format. It is a convenient tool to change the transliteration alphabet of any transliteration file (whether IVTFF-formatted or not) from one to another. The user achieves this by providing a table of equivalences, a so-called "rules file". The tool can apply this table in both directions. Rules files for the common transliteration alphabets are provided with the tool. The user can also define his own transliteration alphabet, and convert any of the existing transliterations into it. A very simple example of that was given here.

The user guide of bitrans is provided here, and the latest source code in C (version 1.4 of 19/09/2021) is provided here.

Please Note that bitrans v.1.2 had a bug and should not be used.

See also the ReadMe file.

Notes

1

See Clemens (2016) and Skinner (2017).

2

See here.

3

See here.

4

See here.

5

I am aware of some efforts in this area in the DECODE database of cipher texts and encryption keys ( >>introduction to the database). These are not yet fully successful (source: B. Megyesi).

6

See Zandbergen (2022).

7

See also the page about the writing system.