Show HN: High-quality duck audio synthesizer(celphase.github.io) |
Show HN: High-quality duck audio synthesizer(celphase.github.io) |
Ducks are named after 'ducking' ... or possibly, 'ducking' is named after Ducks.
edit: also please remove hard ceiling of 120 peas. I want to throw more peas
https://www.etymonline.com/word/duck#etymonline_v_15956
Unrelated but amusing to me: Patak is duck in Croatian, while Batak is "bird" in Sanskrit (but means chicken leg in Croatian).
Another one, in Scots you hear the word "stoor" used for dust, and "sook" for suck. And guess what, in Dutch, they call it a "stoorzuiger" pronounced like "stoor sooker"... :-D
If you speak Scots but you're in Holland or Germany and you want to order more beer, you just say "mair beer!" and it works out the same in the other two languages. This of course works if you speak German or Dutch, and you're in Scotland.
I walk by this business every few days, it's always full of people there. People are happy, in groups and alone, all doing this act of eating.. Not a single problem in sight.
This is a McDonald's restaurant.
Does that mean McDonald's is healthy and good for people?
(..maybe we humans need more signs... )
- Bread doesn't have much nutritional value (especially the kind of white "bread" that is common in the US for example)
- It fills up their stomach fast so they don't forage for foods they would naturally eat
- Throwing bread at one place can lead to overcrowding (which is what happened in your great fishing spot) which stresses the animals
- They also shit a lot in one place, which leads to a bunch of problems
- Uneaten bread causes algae growth which leads to diseases and pests
best to feed them peas like in this neat app or I also heard that cut up frozen grapes are a good choice.
The overcrowding can also allow bird flu to spread more easily.
thank you :-)
I have a chicken farm (and a pig farm but I manage the chickens myself). I want to start a duck farm with a fish pond. Living in a small village and enjoying these things in real life actually changed my life in ways that I cannot explain.
I still (get agents to) write software but my daily life is around the farm and village life (mostly a Sun centric routine). I have to share a bunch of photos, not doing that enough. And I want to record all the bird sounds. Perhaps host a livestream. I live here; the home stay is by the host family: https://maps.app.goo.gl/TEUSdwvko2DRWmou5
https://github.com/celphase/duck-pond
Also replies by author in this sub thread below:
We used to feed the ducks at the lake in the park.
We bought poultry food at the local tack and feed store.
There were dozens of them. When they got spooked and all started flying, the breeze was notable.
Park eventually put in a sign to stop feeding them and took out the benches.
btw i found it works very well as white noise
That then became embedded as an easter egg into some other software.
Ducks were too hard for it though, unfortunately.
Lately, I again threw a clanker at something like that and got it to recreate some MGS codec sound effects.
I'm 0th percentile on the "AIs can feel/are alive" spectrum, but I still think it's probably bad for your soul to use a word that sounds like a horrid slave owner speaking of their property in the 18th century
https://github.com/celphase/duck-pond/blob/main/src/synth.rs
To the credit of the author there is also an attribution file which describes a process of deriving the models from recordings (none of the techniques are very novel, but it's fairly impressive to see automated -- edit: I assume the project is LLM-generated) https://github.com/celphase/duck-pond/blob/main/ATTRIBUTION....
Honestly I can't take credit for any major input on it other than a few technical choices. Audio is entirely outside my wheelhouse beyond what happens at the platform API level.
The process involved running the LLM in a loop to gradually correct parameters of a synthesis stack to have the spectrogram of the output match the spectrogram of a real recorded sample. One funny part is where the synthesis was marked by a classification model as more duck than the real duck sample.
The quality of a recording can throw off most classifiers.
Models we have today are so dependent on the quality of training data, that it's questionable how we will sustain long term what we are currently calling "AI".
i.e. What happens when the cameras and microphones everyone has in their pockets are significantly higher quality and the AI model hasn't had a total refresh in a long time? How does that cause classification to drift enough to fail?
I guess if you are serious about it you can spread it out and drop your peas in different areas and/or don't drop a huge amount at once.