Wooden Aramaic Lord’s Prayer Bracelet

So… we got a Glowforge. And I couldn’t help myself. I’m thinking I should make some of these in olive wood.

Since it’s so much lighter than the metal version (and not nearly as hard to make) I might change the design so that it’s made out of 12 one-sided plates rather than 6 double-sided ones.

What do folks think?


Pope Francis Suggests “Change” to Lord’s Prayer


So I’ve been asked a lot about this lately – especially because of my own attempts at understanding the Lord’s Prayer in Aramaic – and my initial reactions were mixed. However, after my mind settled I did realize that this suggestion had genuine merit.


For those of you who are only casually familiar with what this is all about, Pope Francis made a suggestion about the traditional rendition of the Lord’s Prayer, specifically the phrase “lead us not into temptation.”

His argument was that, “It is not He that pushes me into temptation and then sees how I fall. […] A father does not do this. A father quickly helps those who are provoked into Satan’s temptation.”

His proposed solution was to alter the translation to, “Do not let us enter into temptation.

The Language in Question:

The Greek, on its face, doesn’t seem to quite support this, using the word εἰσφέρω, which is usually rendered as “to lead into” or “bring into.” However, it is this word that is often used to translate the Aramaic verb עלל /’alal/ – and it is this verb that we see used in Aramaic renderings of the Lord’s Prayer (the Peshitta, the Old Syriac, and the Christian Palestinian Aramaic New Testament), as well as other similar petitions in other Jewish prayers.

Where it can mean and is extensively used to express “to bring in” the primary meaning of עלל, is “to enter.”

Because of this עלל is the verb I chose for my own reconstruction of the Lord’s Prayer, however even in doing so, the form I chose was assuming that the Greek had chosen the appropriate nuance.

The Conclusion:

Do not let us enter into temptation” in my own opinion, is – when the original languages are taken into consideration – an appropriate translation of the Lord’s Prayer, and could quite possibly express the original intention of the petition.


Call For Crowsourced Help! – Galilean Dictionary Project

“We need you!”

If you’d like to help out with the Digital, Interactive, and Topical Galilean Aramaic Dictionary project now you can!

If you are good at:

  • Finding free-to-use images.
  • Searching through Aramaic citations for glosses or orthographical variants.
  • Double-checking categories and spotting mistakes or duplicates.

Email me at AramaicDesigns@gmail.com and I’ll assign you a block of word IDs and a task (images, orthography, glosses, categories, duplicates, etc.) from the list over on the RVCC server.

We need these boxes checked off. 🙂

You’ll get your name and a link on the RVCC page under the Contributors section ranked by number of contributions.

Any amount of help is appreciated. We have over 600 words to gather data for.

Spread the word!


Initial Dataset Posted

I’ve gone ahead and updated the dictionary site on the RVCC server. Added a bit of CSS to make it easier to read, and then added a table that represents the initial dataset.

Presently the table is populated directly from a JSON file and as I add things into the list, the JSON file will be updated.


First Steps

(See Digital, Interactive, and Topical Galilean Aramaic Dictionary for the background to this post.)

So how can I get this off the ground?

Figuring out how to tackle this project proved an interesting series of events. When making a general, practical dictionary for people to learn important words, the first question was, “What words does one choose?” The obvious answer seemed to be, “The words that are of the highest frequency in the corpus.” These would be the words that a student would come across the most, and therefore be of most immediate use.

So a few years back I collated the Concordance listings on the Comprehensive Aramaic Lexicon for all of the texts listed in the Palestinian Aramaic corpus.

The Concordance mode merely scans over the requested lemma file (the way that the CAL internally represents documents with lexical tagging), tallies up each instance of the word, and then sorts them in alphabetical order. If one simply collates each of these generated concordances (some 30 or so documents for JPA) and sorts them by frequency, you’re left with a list of nearly 9,400 words for the corpus in order of “popularity.” (I’ll probably post the full frequency list on the dictionary website later.)

Thousands of words are great for print dictionaries, but for a visual dictionary, it was a bit much. The distribution was also extremely skew (as it is for virtually all languages) with many words up front having huge attestation, trailing off into a very long tail of rarely used words, finally ending with a long line of singletons.

Attestation: TOTAL Number:
≥1000 65
≥100 and <1000 469
≥10 and <100 1960
=1 3229

N = 9379

As such, the list needed to be pruned back a bit. I decided to adopt the following two criteria:

  1. The first set of words must be nouns. (This is a visual dictionary, and nouns are easier to illustrate. All verbs, adverbs, prepositions, etc. were tossed from the list.)
  2. An individual word needs to appear at least 5 times in the corpus. (This cut off the aforementioned long tail of some 5784 sparsely attested words.)

Between those two criteria, it brought the list from many thousands of words, down to a “mere” 1,700. This was still a bit much for the initial dictionary in the amount of time I have to complete it.

Additionally, among those ~1,700 words, a large number of them were still tricky to illustrate because they were:

  • Abstract (like “knowledge” or “name” or “obligation”), or
  • Religious jargon (like “Mishnah” or “Torah” etc.), or
  • Otherwise better suited to a separate unit or set in context with its other members (numbers, family, etc.)

A single image slide could not provide sufficient context for these words, so pulling them all out, I was left with a list of about 600 “easily illustratable” words.

This is doable!

The Next Steps:

The List

My next step from here is going to be formatting this list in a readable form for the project’s website. When I start implementing the dataset, this will serve as the “checklist” towards completion and also aid with any crowd sourcing efforts.

Each word needs to have its gloss and orthography checked against the Galilean corpus (sometimes lemma forms diverge, since most lemmas are based off of Eastern Aramaic forms – I’ll put together a list of links), and be broken down into syllable and letter chunks:

(Mockup of multiple spoken hover states. Highlighting, transliteration, and sound would happen in real time depending on where the user hovers the mouse or – if on a mobile device – taps on the word.)

Each word also needs to have its audio recorded.

Once the list is posted, I’ll be sending out a request for help finding images. The images need to be public domain, or otherwise have their copyright released in such a way that they can be used for educational purposes. When this project is done, I’m going to make the source code available for other educators so that they can build their own datasets for different languages, and I want the images to be part of that.

The Test Set

While the full list percolates, I’ll need to compile a small subset of the list – perhaps just a few dozen words – to be the test set. This is what I will use to check to see how the audio will work and to later use as a “dummy” set to implement the interface.

The Audio Chunks

This is going to be, perhaps, the most difficult part.

I’ll need to compile a list of all possible single letter-vowel and syllable combinations and record audio for each one, and then develop some schema to store them so that the software can make use of them.

Luckily, due to the restricted vowel inventory of Galilean, this is a much more attainable task than if it were another dialect. For letter-vowel pairs, it’s roughly 120 combinations (and since that’s doable, that’s where I’ll start). With full syllables, however, I may be looking at 2,500 possible combinations total. Ugh… First things first, though.

The Interface

Finally, with the test set in hand, I’ll start working on the actual code driving the visual interface based off of the initial mockups. This, I anticipate, is going to be one of the easier and fun bits to get done, but when I do sit down to it I’m going to post another update about the design process.

User Testing

This is where everyone else comes in. Once I have a prototype up and running, I need you – yes YOU, reader on the Internet – to help me test it, break it, and reform it stronger. With every successive wave of testing, it will become a better tool.

Wish me luck. 🙂