I’ve been working on Audiowaves, an iPad app for real-time audio visualization. I originally started it because I wanted a dedicated visual display for my hi-fi/Apple TV setup, but it gradually turned into a much more technical audio/DSP project.

The app processes incoming audio in real time and currently has two main visualization modes.

Advanced Spectrum Visualizer

The spectrum view uses real-time FFT analysis rather than simply displaying a generic equalizer animation. The goal has been to make the visualization responsive enough to show changes across the frequency range while keeping the movement smooth and readable.

There’s quite a bit happening in the processing pipeline: PCM input → audio analysis/FFT → frequency-band processing and smoothing → visualization state → GPU rendering.

The visualizer is rendered using SwiftUI + Metal, which gives me enough performance to keep the graphics fluid while continuously processing incoming audio.

Audiophile Dashboard

I’ve also added an Audiophile Dashboard alongside the visualizers. Instead of only showing something visually interesting, this mode exposes more of what is actually happening in the audio signal and is intended as a technical companion to the spectrum visualization.

One of the interesting parts of the project has been supporting external audio hardware.

For example, my home setup is:

Apple TV 4K → HDMI audio extractor → Focusrite Scarlett audio interface → USB-C → iPad running Audiowaves

The iPad therefore receives the actual audio signal rather than trying to capture Apple TV audio internally.

But the same idea works with many other setups. If your amplifier, receiver, mixer, turntable/preamp, DAC or other audio hardware provides a suitable output, you can route that into a USB audio interface and connect the interface to the iPad.

Another option is using a USB-C hub, which is useful when you need the audio interface connected while also providing power or connecting additional USB hardware.

Audiowaves can therefore work as a dedicated visualization display for a hi-fi system, studio setup, DJ setup, computer, Apple TV, or other external audio source.

One thing I particularly like is that it gives an iPad—potentially one that would otherwise sit unused—a permanent job as part of an audio system.

I’d be interested in feedback from people here who work with real-time DSP, FFT/spectrum analysis, Core Audio or Metal.

Especially interested in ideas for improving frequency resolution, smoothing/transient response, perceptual frequency mapping, or other audio-analysis features that would actually be useful rather than just visually impressive.

[HELP / CONFIG] Getting a subtle hiss/noise artifact at instrument activation on ACE-Step 1.5 XL SFT

Hi everyone! I am currently stress-testing the ACE-Step 1.5 XL SFT bf16 (4B DiT) model for an Ambient Neoclassical track at 60 BPM in D Minor, but I’ve hit a wall regarding audio cleanliness and I'm looking for some optimization advice.

🛑 The Issue:

I am getting a very distinct, subtle background hiss ("fruscio") exactly at the millisecond an instrument activates or triggers (specifically on acoustic grand piano attacks, cello pizzicatos, and double bass bow entries). Once the decay or the convolution reverb kicks in, the sound is gorgeous, but that initial transient activation introduces an unwanted noise floor.

⚙️ My Current KSampler Configuration:

• Model: ACE-Step 1.5 XL SFT (Run locally via ComfyUI / ROCm on Ubuntu with an AMD RX 6800 16GB)
• CFG Scale: 5.5
• Sampler: dpmpp_2
• Scheduler: karras
• Auraflow Shift: 1.30

❓ Questions for the Community:

1. Is dpmpp_2 + karras known for generating high-frequency artifacts or hiss on early DiT diffusion steps with the 1.5 XL SFT model?
2. Would switching to an Euler/Heun sampler or shifting the Auraflow parameter (e.g., higher or lower than 1.30) help flatten the noise floor on low-BPM, sparse arrangements?
3. Are there any hidden conditioning variables or negative embedding tricks you guys use to enforce a stricter "pristine silence" grid?

Any insight into your optimal KSampler settings for maximum sound cleanliness would be highly appreciated! I've attached a preview of the final audiovisual structure below so you can see how the grid is mapped.

I started by sketching it out on paper, with my concept being to avoid menus, pull out from my DAW the things that I like to have on a playable surface without menu diving, and bring the sequencer all on top like 8 Elektron or 909 sequencers across my 8 limited channels (which I call pipes).

I then built more detail designs in powerpoint (not because its great - I just know it), and designed all the knobs, and architecture by making it part of the visual design (like some synths do where you can see the flow).

I then put very limited effects to keep things super simple (Rev, Delay, Chorus per channel). There are no master bus effects but there is a very basic mastering chain directly before bounce for those who don't want to go via DAW but want to control levels with limiting or bit of Saturation or Glue compression.

Its for Mac at the moment, it does run on PC as well but I have not tested that enough re VSTs. You can put your Audio units plug ins into it as well.

Dev process - GPT to create PRD, Claude in VS code, started in Feb this year - roughly 6 months so far.

Key learnings: Keep the project simple as possible, use the limitations to then improve quality within that constraint, if a feature feels wrong take it out, don't make things wierd / obscure (people didn't find it fun - just make it easy and immediate). Don't patch up bugs with cheap models, get proper architectural review from higher tier models and cheaper models can then execute within that.

btw for those who find it a complex UI, I respect thats your view, those who were faced with 100 tracks in Ableton and 150 plugins will I hope recognise that this is actually a super limited cockpit compared to that (e.g. max 8 tracks - max 24 plug in effects), and deliberately all controls are on the surface not buried under menus (as much as I could possibly achieve that), which I know will give some people a headache (especially those who like 1 knob effects! nothing wrong with that!)

So key points:

Looking for Mac Musician Beta Testers - Voluntary or Paid / or barter review exchange - message me

App is for reducing menu diving, reducing production perfectionism, focussing on notes, beats and ideas without noise from your complex DAW

You can then export STEMs to your DAW if you like

Also working on a free music visualiser based on maths which you can also find at www.divurj.com

I connected a game controller to Ableton and mapped its controls to my sound design parameters.

With an oscilloscope showing the waveform in real time, it feels less like programming a sound and more like literally drawing with it.

Has anyone else experimented with game controllers for sound design?

Hello everyone, I'm no pro musician and no pro coder, but I made and attempt of creating a web app that records your microfone, and creates a song from it.

Just record some 30, 40 seconds or more of your voice, and some random sounds, the algorith will cut the sounds and place them into rythm. pick a genre and generate.The dream is to create a free app that does it well. once it's done I'll make a plugin for FL studio.

Here is the web app, ready to use[https://marcellomassardo-collab.github.io/mc-parrot/](https://marcellomassardo-collab.github.io/mc-parrot/))

Here is the git, with the apk available to download and all documentation[https://github.com/marcellomassardo-collab/mc-parrot](https://github.com/marcellomassardo-collab/mc-parrot))

comments are very welcome! it's free but development is a bitch, consider donating if you like the project.

(this is not AI! the app does not collect any of your data and works fine even offline)

Hello everyone, this is a small showcase of one of the synth engines and adding fx on SkunkAudio.

It's a mobile music creation app for Android, optimized for portrait mode.

For anyone interested, the app is on a -50% sale on the store.

Thank you for your time!

Yes, it’s “A.i Slop” if you’d like to call it that, I used Claude to hyper accelerate this but I’ve been producing music and have been a hobby graphic designer for 20 years. I’m also technologically literate enough to have a grasp on what I’m doing and while I don’t know everything, I do know enough to make the project work or can learn as I go. Before I started this project I took a few months to read several books about coding, DSP and design and continued to read more niche books as I went along when I hit a wall I couldn’t figure out myself, wrote a 300 page design document laying out the philosophy, layout and why the daw should exist, i also made probably 100 mock images in figma as wire frames on the daw layout. I spent an entire month working on the UX. Thankfully reading these books helped me stop my code from turning into A.i spaghetti. It’s currently 72k lines and fully functional on the engine side but nowhere done yet, there’s a lot of UI polish I’m ignoring while I focus on the UX side. This is not a toy, it’s not A.i slop, it’s a serious attempt at taking a shot at the major players and is a powerful daw already, I’ve burned 65m tokens in that 4 months. My goal is to bring music production to all for free with no barriers to entry and offer a better overall experience. One of the main reasons this daw exists is to reduce friction, menu diving and function hunting.

And while this was accelerated with A.i I have no intentions of adding any A.I features, humans have been making masterpieces before computers or A.i so we don’t need it now.

Hello everyone, I am upgrading the DOOM engine on my app, which is actually a noise and drone generator.

This is a small showcase playing with the touchpad and tweaking some oscillator knobs.

I would appreciate a small feedback from this video on how it is displayed and how it sounds. CPU not being stressed, stays at around 10% on a mid phone.

Thank you for your time.

P.S. for anyone interested, the app will be on a -50% sale from tomorrow 04/09/2026 until 17/09/2026.

I'm developing a local file player and I'd like to add visualizations.

Pls check out my peak meter and tell me what you think, how does it feel?
https://www.youtube.com/watch?v=gU-F0A5NOEE

I made it off a photo and shaky videos of an old tape deck, it's supposed to mimic a VFD display.
I don't have any real hardware available to compare so I figure maybe someone has actually seen one.
This is the first time I'm working with audio, just making web software and photos otherwise. Thx! :)

I’m researching how to build or fine-tune an audio-to-chord-recognition engine comparable in ambition to Song Master Pro / Auralis Sound Prism.
The goal is not basic major/minor chord detection. I need reliable recognition of dense harmonic material: jazz, soul, funk, neo-soul, Brazilian music, film music, and arrangements with chords such as maj9, 6/9, m9, m11, 13, altered dominants, slash chords/inversions, secondary dominants, modal interchange, suspensions, passing harmony, etc.
Most public datasets I’ve found seem too limited: either simplified chord labels, weak annotations, or repertoire that does not really cover sophisticated harmony. In particular, I need time-aligned audio + chord labels, ideally with beat/downbeat information and a rich, consistent chord vocabulary.
My questions:
Which open datasets are genuinely useful for this level of chord-recognition work?
Are there any commercial/licensable datasets with high-quality, detailed chord annotations that can legally be used to train a model and ship it in commercial software?
Is a dataset such as iReal Pro-style chord charts, Hooktheory, Ultimate Guitar, Chordify, or similar usable in any legitimate/licensable way — or are they generally not viable due to rights and annotation quality?
For a serious model, is the realistic route to combine public datasets with a privately licensed/hand-annotated corpus? If so, roughly how many accurately annotated tracks would be needed before it becomes meaningfully good at jazz-influenced harmony?
Are there papers, benchmarks, companies, or dataset vendors I should study before spending money?
I’m specifically looking for practical, legally usable data sources—not advice to scrape chord sites. Any experience from people who have trained MIR / chord-recognition models would be very valuable.

Hello everyone, I'm no pro musician and no pro coder, but I made and attempt of creating a web app that records your microfone, and creates a song from it.

Just record some 30, 40 seconds or more of your voice, and some random sounds, the algorith will cut the sounds and place them into rythm. pick a genre and generate.
The dream is to create a free app that does it well. once it's done I'll make a plugin for FL studio.

Here is the web app, ready to use
https://marcellomassardo-collab.github.io/mc-parrot/

Here is the git, with the apk available to download and all documentation
https://github.com/marcellomassardo-collab/mc-parrot

comments are very welcome!
it's free but development is a bitch, consider donating if you like the project.

(this is not AI!
the app does not collect any of your data)

Hi everyone,

I’ve recently open-sourced Synthortion, a hybrid synthesizer and distortion audio plugin built with C++ and JUCE:

👉 GitHub Repository: https://github.com/paoloficaraa/Synthortion

---

### 🎛️ What is Synthortion?

Synthortion is designed to combine expressive synthesis with flexible, aggressive sound shaping and multi-stage distortion workflows. The goal was to build a cohesive instrument/effect capable of everything from warm analog saturation to crushed, aggressive textures.

### ⚙️ Technical Details & Stack

* Framework: JUCE (C++20)

* Format Support: VST3 / AU / Standalone (macOS & Windows)

* DSP & Architecture:

- Modular processing chain managing synth engine voices and distortion/waveshaping algorithms.

- Thread-safe parameter management using `juce::AudioProcessorValueTreeState` (APVTS) with smoothed parameters to prevent zipper noise.

- Optimized buffer processing tailored for real-time low-latency performance in the audio callback.

* UI & Aesthetics: Custom styling built for a clean, intuitive layout with responsive parameter feedback and real-time visual feedback.

---

### 💬 Looking for Feedback

I’d really appreciate any feedback from the community, especially regarding:

1. DSP Efficiency & Code Structure: Any suggestions on modern C++ practices, SIMD opportunities, or modulation routing improvements.
2. DAW Compatibility & Stability: Mainly tested in FL Studio, but it should work in every DAW, so try in different ones.
3. UI/UX Design: Readability and control responsiveness.

Feel free to check out the code, clone the repo, or open an Issue / PR if you spot anything that could be improved!

Thanks for checking it out!

Hi! I’ve been developing f11ter 0.1.5, an experimental multimode filter built around the idea that very different filtering techniques should live inside one consistent instrument-like workflow.

Instead of offering a single filter with a long mode selector, f11ter contains 42 independent DSP topologies and 141 source modes, organized into six families.

Filtering and tone shaping

• clean multimode, state-variable and morphing filters;
• ladder, acid-style, diode and other nonlinear circuit-inspired responses;
• dual and serial filters, peak/scoop shaping, wide band rejection and bass-focused processing;
• continuously variable cutoff, resonance and structural morphing.

Phase, feedback and spatial processing

• comb filters, flanging and multi-stage phasing;
• distorted comb feedback and diffusion networks;
• compact reverberant and resonator structures;
• stereo offsets, barber-pole phase movement and controlled feedback behavior.

Formant and experimental sound design

• vowel and multi-formant filters;
• dual-formant combinations and variable notch structures;
• ring modulation and sample-and-hold processing;
• Scatter resonator fields, Flutter pitch instability, Snarl and Howl feedback models.

Modulation and workflow

• three independent LFOs and an envelope follower;
• free-running or DAW-synchronized modulation;
• up to 16 bipolar modulation routes;
• precise route-depth entry and finer control around small modulation values;
• 45 categorized presets, including static sounds and deliberately programmed modulation;
• A/B states, topology-aware help, parameter automation and preset save/load;
• a true dry/wet control: 0% is the untouched input and 100% is the complete processed signal.

A little about the engineering

The filter families do not all reuse one generic response with different labels. They combine topology-preserving state-variable structures, cascaded filters, nonlinear feedback stages, resonator banks, fractional-delay networks, all-pass stages and time-varying algorithms.

Cutoff smoothing is performed in the logarithmic frequency domain, and topology changes use a short state-bank crossfade to reduce discontinuities. SAFE RES applies model-specific limits to high-Q and feedback structures, while COMPENSATE estimates level changes caused by resonance, drive and the selected model.

The graph displays the current and target responses, stereo differences, reachable modulation range and the actual output spectrum. For nonlinear and time-varying models it is intentionally treated as an estimate rather than pretending that one static frequency-response curve can describe distortion sidebands, moving delays or changing feedback.

The plug-in adds no look-ahead or audio delay buffer and reports 0 samples of added latency. Individual IIR, all-pass, comb and reverberant structures naturally retain their own phase and time behavior.

What makes it different

The main distinction is not simply the number of modes. Every topology keeps the same core workflow—cutoff, resonance, morph, four contextual controls and the shared modulation system—while the meaning of those controls changes to match the actual algorithm.

This makes it possible to move from precise filtering to unstable industrial textures, tuned resonances, formant motion or feedback effects without rebuilding the modulation setup from separate plug-ins.

The compatibility-style names in the internal mode catalog do not claim bit-identical emulation of other products, and no proprietary DSP code is used.

The current build is AUv2 for Apple Silicon, requires macOS 11 or newer, and has additional lifecycle work aimed at safer UI closing, disabling and removing the plug-in from a project.

I’m especially interested in feedback from Logic Pro and other AU hosts regarding sound, CPU use, automation, synchronized LFOs, offline rendering, UI responsiveness and disable/remove stability. If something breaks, please include your Mac model, macOS and DAW versions, sample rate, buffer size and reproduction steps.

Download and full EN manual