u/SpecialNothingness

I'm playing a choral prelude(Elias Oechsler, link below) and there are several "Th." in the score. According to search it might have to do with coupler or division, but given that hint I still don't know what they're telling me to do.

Also, this one has many collisions (a long note being interrupted by another note of the same pitch). Am I missing something here?

IMSLP 654071: IMSLP654071-PMLP1048929-oechsler3.pdf

I'm not posting this to annoy organ specialists here. But to leave accessible information for somebody who might find this useful. Somebody without access to traditional organs. Somebody who mainly wants to play like me in the video.

This was 3D printed and assembled today. Very straightforward, easy to build, and compact. A spacing of 6cm works completely fine (for me), fitting 24 notes in a little over 80cm width. No need for a special chair. I have put blender files and Arduino source here: https://github.com/h2kyeong/scriptlets/tree/main/button_pedalboard

My findings which may help others who may attempt to design their own pedal board:

• KY-003 hall effect sensors operated well for me with 3.3V of voltage, which is less than standard 5V. Separation by 1cm and a plastic wall is no problem if you use neodynium magnets.
• Springs can be U-shaped attachments under each key, and need to be softer than I initially thought.
• Soldering is hard. Breadboards and jumper cables make connections much easier.

Compared to the AGO specification, I removed concavity in the "tilting to the side" direction, because gravity might increase friction to one wall. And I made the bars parallel, because otherwise keeping consistent width of walls might be more difficult. I shortened the bars by a lot to save space.

Due to lack of experience, I don't know how playable this pedal board is compared to others.

Designing and building (up to this point) was easier than I feared. But that was because I purchased a 3D printer.

I'm starting a more authentic design.

Understanding the bar positions is the starting point. Does it look correct?

def test ():
     a = []
     r = 50
     step = 0.02
     origin = (pi - step * 31) / 2
     for i in range(32):
         th = origin + step * i
         a.append(( cos(th)*r, sin(th)*r, 47 -sin(th)*r ))

edit:

Due to the combined curvature on the Z axis, the spacing between keys is not uniform in the above. I should use scipy solver to get corrected angles to make them uniform.

The number 32 is not what I need. An octave consists of 14 halftone intervals and thus between C to G we have 36 half intervals of 1.25 inches.

I decided to DIY a pedal board. But using arcade buttons instead of wood bars. The quick picture above shows one octave, but I'm thinking full 32 notes.

I have ordered "Teensy 4.1 with pins", enough buttons for 32 notes, 15 m of 24 AWG wire, and a soldering tool. I'm considering ordering wood planks with CNC holes according to the scheme above. But before doing so, I wish for advices from organ players for improvement.

• Is 6 cm spacing optimal? The buttons are 3 cm in diameter.
• Should the elevated "black keys" be separated by space?
• What might be the optimal elevation height?
• Would arching the overall shape drastically improve usability?

I made gemma4 12B write timestamp-anchored summaries of youtube video transcripts. I tested if the summaries have significant qualitative variance and if the SLM can pick the best one by itself. Below is the prompt texts I used.

"{{[INPUT]}}<attachement name='original'>", document,
"</attachment>Above is a transcript. Divide time ranges by topic and name subheadings. Insert brief summary under each subheading.{{[OUTPUT]}}",
"{{[INPUT]}}",
"<attachment name='Summary A'>", ans1, "</attachment>",
"<attachment name='Summary B'>", ans2, "</attachment>",
"Above is a transcript and two summaries A and B. Name the better summary. The most important quality of an excellent summary is presenting the core message that is unique to the video. No explanation is required.",
"{{[OUTPUT]}}"

Here are my findings.

(1) The judgments were biased to favor the latter example. To counter this, I added another round of comparisons where the candidates were swapped.

(2) After balancing, the judgments were not random and significant. Making it justify the choice before the final verdict is not necessary. Probably an all pairs comparison (quadratic time) is not necessary for finding the best one. For instance, one could rank 5 candidates and take the best one and generate 4 more to form the next 5.

To evaluate the wins and losses, I used Maximum Likelihood Estimation (MLE) based on Bradley-Terry model.

Just in case somebody wants it, here is the code: https://github.com/h2kyeong/scriptlets/blob/main/llm_multigen_league.py

Buttons like these could serve the purpose if they are put in the right positions. Or so I imagine. Gotta be better than nothing, right? Has anyone tried something like this?