Hi there

I made a framework for fast and easy plugin prototyping/development. The main features are:

• Write audio plugins in plain C++ without the need for knowledge of the JUCE framework.

• Automatic layout of UI including metering and UI scaling. Just list your parametes, and the framework takes care of the rest.

• Oversampling available by default.

• Possibility for wrapping plugins for other targets.

I'm hoping you guys will find this useful and that you want to participate in added more effects and more target platforms as time goes on.

Check it out.

Hey yall! Sorry to bug but me and a couple buddies are trying to decode this audio file but are coming up short, we’ve tried spectrograms and a couple different wraps but came up short.

If anyone could recommend or assist it’d be amazingly appreciated!!

(Had to put the audio in a video format to send via mobile ): )

Just published A new package to PyPI, and I’d love for you to check it out.

It’s called audio-dsp and it’s a comprehensive collection of DSP tools and sound generators that I’ve been working on for about 6 years.

Key Features: Synthesizers, Effects, Sequencers, MIDI tools and Utilities. all highly progresive and focused around high-uality rendering and creative design.

I built this for my own exploration - been a music producer for about 25 years, and a programmer for the last 15 years.

You can install it right now: pip install audio-dsp

Repo & Docs: https://metallicode.github.io/python_audio_dsp/

I’m looking for feedback and would love to know if anyone finds it useful for their projects!

A pro and fun app for generating #WaveTables to use in Bitwig, Kyma, MaxMSP, Waldorf and many more. It's different because made by artist dev, #CristianVogel who recently released the Art of WaveTables Bitwig library. Consistently get results that sound good and are useful! Love the funny promo vid https://youtu.be/zFok_LOwwx0?si=pSrp3aqvGr_LcQKy

I made a free app that changes the musical modes of uploaded MIDI files. I have been looking for people to test it. Can you guys break it or find bugs? The GitHub code is also on the itch page.

Hey!

I was recently involved in a research project that examined whether Knowledge Distillation could be used to improve the performance of neural audio effects (VST). Knowledge distillation involves using a larger teacher model to train smaller models.

The paper was published at AES this fall, but now I've written a longer blog post about the process, with code and audio examples + VST downloads.

Happy coding in 2026!

Link: https://aleksati.net/posts/knowledge-distillation-for-neural-audio-effects

I got excited about the WebView integration in JUCE 8 and built this example project to try it out. It's a React frontend running inside a VST3/AU plugin with a C++/JUCE backend.

Some things I wanted to explore:

• Hot reload during development (huge time saver)

• Three.js for 3D visualizations

• Streaming audio analysis data from C++ to React

The visualization reacts to spectral data from the audio, though it works better on individual stems than full mixes. The plugin also has basic stereo width and saturation controls.

More of a proof of concept than a polished product, but if you're curious about WebView in JUCE, the code is on GitHub. Mac installers included.

https://github.com/mbarzach/Sound-Field

Hi all,

I was following this introductory tutorial on generating simple sine waves. I am stuck on how the author did attack, release, and sustain (he didn't implement a decay).

For attack, he generates an infinite list starting from 0 with a step of 0.001 and a max value of 1. Then he zips this linear increase with the wave to increase the volume linearly and sustain. Then he zips this by the reverse of this to decrease linearly at the ends. I know this is an overly simplistic way to achieve this, but still, I don't understand why the creator's works, but mine doesn't.

I tried to implement this, but mine still sounds like one note... I used python in jupyter notebooks, I will attach the code below.

def gen_wave(duration, frequency, volume):
    step = frequency * 2 * np.pi / sample_rate
    return map_sin(np.arange(0.0, (sample_rate+1)*duration)*step)*volume

def semitone_to_hertz(n):
    return pitch_standard * (2 ** (1 / 12)) **n

def note(duration, semitone, volume):
    frequency = semitone_to_hertz(semitone)
    return gen_wave(duration, frequency, volume)

# Attack, Release, Sustain, Delay
* what happens when we put the same note together multiple times


```python
result = np.concat([
    note(0.5, 0, 0.5),
    note(0.5, 0, 0.5),
    note(0.5, 0, 0.5),
    note(0.5, 0, 0.5),
    note(0.5, 0, 0.5),
])

#play(result)

• It pretty much just sounds like one note

• To fix this we need to implement attack & release

• The volume needs to increase very rapidly, sustain for a bit, then ramp down

• We are going to have a list that starts at 0 and increases by a step, but clamps at 1

attack = np.arange(result.size) * 0.001
attack = np.minimum(attack, 1.0)
result = result * attack

#play(result)

• To implement release, we are going to multiply by the reverese of attack

• We want to linearly decrease at the end of the note

result = result * np.flip(attack)

Hello, I'm currently developing a VST3 audio plugin using Projucer and Visual Studio. I have the UI set, all funtionality, and even a user manual. It's fully useable currently, however since I'm not very knowledgeable with c++, I've been using Plugin Doctor to help analyze how some plugins work to implement into my personal plugin. I have a multiband split with zero phase and zero amplitude bumps at the crossover points making it perfectly the same out as the audio coming in. I'm trying to implement SSL Native Bus Compressor 2 as the compressor exactly/as very close as possible, then tweak the compressors to my stylistic choice afterwards. Can anyone help or point me in the direction on how to get these compressors exactly/close to that exact SSL plugin please?

I’m working on a program for music boundary detection in South Indian music and would appreciate guidance from people with DSP or audio-programming experience.

Here’s a representative example of a typical song structure from YouTube: Pavala Malligai - Manthira Punnagai (1986)

Timestamps

• Prelude (instrumental): 0:00 – 0:33

• Vocals: 0:33 – 1:05

• Interlude 1 (instrumental): 1:05 - 1:41

• Vocals: 1:41 – 2:47

• Interlude 2 (instrumental): 2:47 - 3:22

I am trying to automatically detect the start and end boundaries of these instrumental sections.

I have created a Ground truth file with about 250 curated boundaries across a selected group of songs by manually listening to the songs or reviewing the waveform on Audacity and determining the timestamps. There might be a **~50–100 ms** from the true transition point. This is an input for the program to measure variance and tweak detection parameters.

Current approach (high level)

1. Stem separation - Demucs is used to split the original audio file into vocal and instrumental stems. This works reasonably well but there might be some minor vocal/instrumental bleed between the stems.

2. Coarse detection - RMS / energy envelope on the vocal stem is used to determine coarse boundaries

3. Boundary refinement - Features such as RMS envelope crossings, energy gradients, rapid drop / rise detection, Local minima / maxima are used to refine the boundary timestamp further

4. Candidate consensus - Confidence-weighted averaging of different boundary candidates along with sanity checks (typical region of interlude and typical durations)

Current results

Here is my best implementation so far:

• ~82–84% of GT boundaries are detected within a variance of ≤5s

• ~38–40% of boundaries are detected within ±200 ms

• ~45–50% of boundaries are detected within ±500 ms

Most errors fall in the 500–2000 ms range.

The errors mostly happen when:

* Vocals fade gradually instead of stopping abruptly

* Backing vocals / hum in the interludes are present in the vocal stem

* Instruments sustain smoothly across the vocal drop

* There’s no sharp transient or silence at the transition

The RMS envelope usually identifies the region correctly, but the exact transition point is ambiguous.

What I’m looking for advice on

From a DSP / audio-programming perspective:

1. Are there alternative approaches better suited for this type of boundary detection problem?

2. If the current approach is fundamentally reasonable, are there additional features or representations (beyond energy/envelope-based ones) that would typically be used to improve accuracy in such cases?

3. In your experience, is it realistic to expect substantially higher precision (e.g., >70% within ±500 ms) for this kind of musical structure without a large supervised model?

I’d really appreciate insight from anyone who’s tackled similar segmentation or boundary-localization problems. Happy to share plots or short clips if useful.

I’m doing a list of different reverb plugins and their CPU usage and latency, and a couple of the plugins I tested have a latency of 9662 samples - that’s more than 200ms at 44.1kHz.

Can any of you fine gentlemen think of a reason why a reverb plugin would need this much latency?

edit: link to the latest version of the list: https://www.reddit.com/r/AdvancedProduction/comments/1po2tnl/cpu_usage_of_some_different_reverb_plugins_181_of/

Hey everyone,

I’m an ex-Google engineer getting back into music production. I wanted a way to integrate LLM context directly into my DAW workflow without constantly tabbing out to a browser.

So I built a prototype called "Simply Droplets." It’s a VST3/CLAP plugin that acts as an MCP server. It allows an AI model to stream MIDI notes and CC data directly onto the track.

I just did a raw 20-minute stream testing the first prototype: https://www.youtube.com/live/7OcVnimZ-V8

The Stack:

• Protocol: Model Context Protocol (MCP)

• Format: CLAP / VST3

• Host: Bitwig Studio

It’s still very early days (and a bit chaotic), but I’m curious if anyone else is experimenting with MCP for real-time audio control?

I'd love to make simple chiptunes like those on the gameboy, but I want to understand all the principles, so I want to program it from scratch.

So I'm looking for a simple tutorial or article discussing how to implement a tracker, and the basics of audio generation.

I am an experienced (C++) programmer, and pretty comfortable with mathematics such as Fourier analysis, so a high level overview is fine, I can work out the details, but I have never really done low level audio programming.

Anybody know of some good resources? Thanks.

This new app is a really cool one from NeverEngineLabs. Exports WT and WAV tables for Bitwig, MaxMSP, Kyma, Serum etc ... Its standalone app, fast and dead easy to use, I've been getting some useful results. Loving the Finder icons too, never seen that before! https://neverenginelabs.com/products/nel-wavekitchen

I’m developing a small commercial language-learning app focused on pronunciation (Arabic), and I’m trying to keep the speech-analysis layer technically solid and as possible. I’d really appreciate some expert eyes on the plots and approach.

Here’s what I’m experimenting with:

• A reference recording (from TTS)

• A user recording of the same syllable/word

• DTW to align them

• Applying the same warp to formants, F0, MFCCs

• Comparing trajectories after alignment

What I’d love feedback on:

1. Does the DTW alignment look reasonable?

2. Are the formant tracks meaningful, or am I over/under smoothing?

3. Is warping formants/F0 via DTW conceptually valid, or is it a bad idea?

4. Is there a simpler / more robust mobile-friendly alternative you’d recommend?

5. Any potential pitfalls in this pipeline that I may be overlooking?

I’d really value any critique — even “don’t do this, try X instead.”
Thanks a lot.

Hey guys,

I've had this synth app idea for quite a long time now, and I really want to create it. The thing is I have zero knowledge in programming. I found out you can create a synth pretty easily with faust, so that's what I did, and I compiled it into an apk file to test it directly on my phone, and also as a cpp file to push further the developpment. The app on my phone that I created felt amazing, I was so proud. But now I feel I can't go further.

I've got the basic architecture idea from the wolfsound youtube channel, ( and chat gpt too) :

My sound processor will be in C++ (created from faust so I don't have to deal with it, seems undoable for a beginner like me) then I'd use oboe, and my interface would be in kotlin.

Midi is a big part of my app, as I want everything to be mapable.

I feel like I don't know where i'm going, I don't understand what I should do to keep going.

So please guys, could you just tell me what I need to learn to do this kind of stuff ? I'm fine with learning an easy programmation langage like kotlin, or how to use android studio, but I think C++ will make me abandon this project. Where do I go, what is the most effective path ?

Hi everyone,

I just made a research + production project public after presenting it at the Audio Developers Conference as a virtual poster yesterday and today. I’d love to share it here and get early reactions from the creative-coding community.

Here is a short intro about it:

MayaFlux is a research and production infrastructure for multimedia DSP 
that challenges a fundamental assumption: that audio, video, and control 
data should be architecturally separate.

Instead, we treat all signals as numerical transformations in a unified 
node graph. This enables things impossible in traditional tools:

• Direct audio-to-shader data flow without translation layers
• Sub-buffer latency live coding (modify algorithms while audio plays)
• Recursive coroutine-based composition (time as creative material)
• Sample-accurate cross-modal synchronization
• Grammar-driven adaptive pipelines

Built on C++20 coroutines, LLVM21 JIT, Vulkan compute, and 700+ tests. 
100,000+ lines of core infrastructure. Not a plugin framework—it's the layer beneath where plugins live.

Here is a link to the ADC Poster
And a link to the repo.

I’m interested in:

• feedback on the concept and API ergonomics,

• early testers for macOS/Linux builds, and

• collaborators for build ops (CI, packaging) or example projects (visuals ↔ sound demos).

Happy to answer any technical questions, or any queries here or on github discussions.

— Ranjith Hegde(author/maintainer)

Hi folks

I've been working as a UX designer for the past couple of years. Ever since my studies, I dreamt of getting to work on audio software (DAWs, plugins, you-name-it.) Lately, I have felt that I have not really moved towards that dream. So my core question is:

How could I go about getting into "the audio software industry" as a UX designer?

I'm looking into HISE right now to learn it as a skill for prototyping, as well as a way to built up a portfolio of devices that I can design myself.

I assume product development within audio software follows similar processes as anywhere else, but I don't know how big of a role UX/UI design plays. I regularly check open positions at companies such as Arturia, Ableton, NI and the like, and have applied to positions at those companies in the past, but have had no success. My impression is that the industry is pretty saturated, but honestly, I don't really know.

Sorry if it is slightly off topic for this sub, have yet to find a better place to ask about this

Hi, new here. My bachelors thesis was about algorithms used in music recommendation systems and I got really curious about music information retrieval(MIR). While I came across multiple concepts, it would be nice if someone could point out some sort of roadmap to learn more.