Doesn't [tabread4~] apply cubic interpolation? If you store a ramp to a table, you could use that with [line~] to read through it, couldn't you?

You can check the [serial_print] abstraction from here https://github.com/alexdrymonitis/Arduino_Pd
If you print your values in the Arduino code properly (see the help sketch), then in Pd you can use this abstraction with a [send] and get your values with a [receive]. Check the exampes, they should be straight forward.

You can also check the audiolab library (available on deken; Help -> Find externals). It's a collection of vanilla abstractions. Its pitch shifter might be a bit CPU hungry as it is FFT based, but it's pretty good.

Since your source is a .wav file, why don't you store the file to an array and use [tabplay] or [tabread4~] to read it in a loop? I'm pretty sure that a [vline~] with a long list will be way more CPU hungry, let alone the complexity needed for something like this.

@porres The main issue that I see with neural networks is the immense amount of data they need to train properly. Apart from being hard to assemble a proper training dataset, there are all these copyright issues and (un)ethical use of data and AI. But in some cases they can be very useful, like controlling lots of parameters with just a couple of knobs (or the mouse pointer position) or messing with sound with variational autoencoders and their latent space, to transform sound in various ways (check the example of this external where the sinewave is turned into a sawtooth - not very clean, but it's just an example), just a couple examples of their use.
Still, I do believe that AI and NNs are a hype that evenrually will phase out and will be replaced by something else that will become the new thing.

@spluta I do have my own project which is an external that enables the creation of neural networks, all written in C from scratch, but I've gone as far as autoencoders, struggling to get it to create variational autoencoders. RTNeural though takes advantage of all the development that has been done in Python packages (the go-to language when it comes to AI), so this external is really nice to have!

This is a great addition to Pd's AI capabilities! I had thought of creating a Pd external based on RTNeural some time ago, but it was too much for me to handle. I'm grateful you took the initiative and did this! Being able to train NNs in Python and run them natively in Pd opens up a lot of possibilities!

What OS are you using? I guess you're trying to open a .pd file from inside your system, not inside Pd, right? Your system launches a new Pd instance for some reason. Did you try opening your patches from within Pd with Ctrl+O (or Cmd+O on a mac)?

@elden I don't think it's very popular. I only remember IOhannes mentioning in on Pd's mailing list. It's just a subdomain of Pd's website, deken.puredata.info, and you can search all of deken (Help -> Find externals) in your browser.

@elden Try the Pd website (the deken subdomain) https://deken.puredata.info/search.html?libraries=list-abs&objects=&descriptions=