reverb | use data storage and transport system | Machine Learning library

To give a bit of context, i am trying to implement in matlab from scratch the following signal diagram, a Feedback Delay Network (FDN). pic: FDN

With an appropriate matrix, indifferent to delay lengths, virtually white noise comes out when fed a dirac impulse.

I've managed to do this in code, but my goal is another and hence my question. I want to apply a filter h(z) after each delay line z^-m. pic: h(z)

More specifically, i want to apply a third-octave cascaded graphic equalizer after each delay line. The purpose is to create frequency dependent attenuation on the whole structure, and consequently delay dependent. I've successfully designed the filter in the form of SOS, but my problem is: how do I apply it within the structure? I assume to use sosfilt() somewhere with what I have, but I'm not sure.

I haven't reduced the order of the system for sake of purpose. The order is 16 (16x16 matrix, 16 delay lines, 31x16 biquad filters)

The first code refers to the lossless FDN, safely runnable which generates white noise. I have commented my failed attempt to introduce the filtering in the loop saying: % Filtering

Unfortunately, I can't post all GEQ entries, but I'll leave 8 in the end corresponding to the first 8 delays.

So, the question is how do I code to filter the white noise, implementing frequency dependent attenuation in the whole FDN structure. Also, although it may be computationally inefficient, I'd prefer to apply this without higher level functions and based on what I already have, i.e: applicable in GNU Octave

Edit: Assuming you have to apply the bandpass 2nd order filtering sample by sample using the difference equation, how would you recursively do it for 31 bands in series? One is shown in the second code section.

We are working on a project which allows us to record some sounds from a microphone with a 5k Hz sample rate with some Low-Pass filter & HighPass filter.

What we are using

We are using AvaudioEngine for this purpose.

We are using AVAudioConverter for downgrading the sample rate.

We are using AVAudioUnitEQ for the LowPass & HighPass filter.

Code

I successfully followed this official tensorflow tutorial for training an agent to solve the 'CartPole-v0' gym environment. I only diverged from the tutorial in that I did not use reverb, because it's not supported on Windows. I tried to modify the example to train the agent to solve my own (extremely simple) environment, but it fails to converge on a solution after 10,000 iterations, which I feel should be more than plenty.

I tried adjusting training iterations, learning rates, batch sizes, discounts, and everything else I could think of. Nothing had an effect on the result.

I would like the agent to converge on a policy that always gets +1 reward (ideally in only a few hundred iterations, since this environment is so extremely simple), instead of one that occasionally dips to -1. Instead, here's a graph of the actual outcome:

(The text is small so I will say that orange is episode length in steps, and blue is the average reward. The X axis is the number of training iterations, from 0 to 10,000.)

Imports

So I have a command for my discord music bot, here's the command:

Getting following error when trying to excecute

i need help debugging this code, i am trying to make an effect where the screen is tinted a blueish color and the reverb is set to bathroom whenever a camera is inside a part named "water", it works for 1 body of water in the game and the rest will not cause the effect to happen, despite it printing for every body of water in the game, im assuming the one it picks to work is the one that is loaded first, but im not sure why only that one registers, it checks for them all but only that one part actually causes it to happen

I am trying to get the data from a binary file (specifically OnlineSequencer's new sequence file format) using Google protocol buffer, but all it's printing is the file size. I have compiled both the .proto files used by it to python scripts: sequence.proto:

I've been working on a project with an Arduino recently where I'm basically trying to get a small display hooked up to an Arduino to update with the name of a MIDI mapped knob in Ableton Live.

For example, let's say I map the knob to the reverb send on a track the display should read "A-Reverb". This works today, but only works when I first open the Ableton project and map the knob for the first time. It does not update when I select a new option.

Here's the setup I'm using right now:

• Arduino - w/Rotary Encoder & OLED Display
• Hairless MIDI - For converting the serial connection from the Arduino into MIDI CC# messages Live can read.
• Ableton Live 11 w/ Max For Live 8 - This is where the patch actually runs.

For the Max Patch, I'm using a version of Yehezkel Raz's One which I purchased and later modified. The reason I mention this is that this patch already has the name updating part worked out, so in theory I should be able to send that data over serial to the Arduino.

Out of respect for Yehezkel's work, I won't attach a screenshot of the entire patch, but have attached the part that I modified to send data to the Arduino, you can see it here.

Here's what I've tried so far:

1. Validated that the baud rate for Hairless MIDI, the Arduino, and the Max Patch is identical
2. Attempted to start Hairless MIDI only after Ableton has been launched
3. Attempted to power on Arduino without opening the Arduino IDE so that there are no Serial conflicts.

Here's what I think may be the issue, but I'm not sure how to fix it:

• Part of the logic in my Arduino code relies on Serial.available() being true, in order to send the data to the screen. I'm thinking that maybe the Serial connection is only available in the beginning when the knob is mapped.

I know that was a lot of information, but if anyone has any ideas on how I may be able to get this to work, I'd greatly appreciate it!

I'm trying to change the bitrate of the given audio file, the following code generate an audio with 1411 kbps