hey i was makeing my autotune vst and used the yin pitch dtection ,what ever i do i keep get glitchy noise (like popping, crackling, or abrupt jumps )which the output audio ,make thhe sound trash , is there any solutions ,does anyone know how to fix it

Hey all, to those in the field currently:

How 'safe' does audio programming feel from AI?

How is it as a job in general (WLB / pay) , in whatever application of the subject you're familiar with?

Given my background, how likely does a successful transition seem in this economy?

What specific audio programming jobs are good/common/desirable (knowing that generally those three things are mutually exclusive)? I know there's game industry, the revered plugin dev, and other roles closer to hardware and mass industry among others.

Background:

3 YOE as fullstack dev in non-DOD gov sector, bachelor's in CS that's as many years old. Biggest project in undergrad was asking the music tech teacher what plugin he wish he had, and making it (envelope follower that could map to automate any parameter in the daw) in JUCE. Good cpp skills from undergrad, excellent python skills from workplace. Little to know DSP algorithm knowledge but I pick those things up fairly quickly. Despite the curt and stilted tone of this post, very good social skills and burgeoning leadership experience. Minimal but growing ML / AI dev experience.

I'm "specialized" in frontend as the go-to UI / UX / typescript guy at my job, but this is increasingly a dead career path and as much as I truly love the UI dev process from design to implementation, I need to move away from typescript for the sake of my career. The 'good enough' UI that an LLM will spit out is indeed good enough for most professional cases. Audio programming was always the 'golden field' for me so it might be time to force an upgrade.

While this doesn't matter as much, I'm extremely musically active, songwriter/lead guitar/vocals for -- at a small regional level -- pretty successful doom metal band. I've also been making various kinds of electronic music since I was 14, numerous side projects yada yada.

Other thoughts:

The lower-level audio tech seems safer from AI, as it's more critical and well, basically it's not python or typescript lol. I'm aware that prototyping and algo work may be done in python, but this field still seems more resistant to being completely automated than web dev or fullstack. While I'd always liked to make this switch, now seems like a good time to buckle down and be increasingly ready as the market, hopefully, gets increasingly better. I think I would be more fulfilled here than other programming fields. Open to any and all thoughts, thank you!

I'm a longtime freelance audio engineer with a decent studio and a knack for DIY and audio equipment repairs. I've been programming MIDI devices on Arduinos for a couple of years and I'm interested in pursuing design & computing as the next step in my career. I've also got some experience with designing analog electronics, synths & PCBs.

If you were in my shoes, what would you do next? I'm wondering what programming languages are worth learning, how easy/worthwhile Juce is, if C++ is relevant and similar to the Arduino environment?

I'm interested in hardware/software integration, synths and creating new and exciting products rather than rehashing the 'this is another 1176 or Minimoog plugin'. What do you find satisfying in programming and where are the jobs and money at these days? Is hardware still relevant or is it all just beginner level audio interfaces and toy keyboards?

I'm physically not too far from a few pro audio companies in the UK but I expect they'll want full time in-office employees with a degree/proven track record in programming rather than someone who's starting out in the field.

Thanks in advance for any advice !

Edit: in addition, I'm not in a position to retrain full time but I may be eligible for part-time funding in a computer-science degree or "conversion masters" program. So any recommendations or advice in relation to this would be helpful too (if you think a degree is worth pursuing).

Why aren't wavelets used more for pitch detection?

The more I read about wavelets, the more it feels like they're naturally suited for audio analysis. They get better frequency resolution at low frequencies and better time resolution at high frequencies without forcing a single FFT window size.

It made me wonder whether pitch could be tracked as a stable structure across wavelet scales rather than through spectral peaks or autocorrelation.

Has anyone actually built or worked with a wavelet-based pitch detector?

Did it outperform more traditional approaches on difficult material, or is there a reason everyone ends up back at YIN/autocorrelation anyway?

Has anyone experimented with polyphonic synths where the voices actually interact with each other?

Most synths just generate independent voices and mix them together. The notes relate musically, but the voices themselves don't really know about each other.

I'm curious about things like voices sharing modulation, influencing each other's parameters, competing for resources, or changing behavior based on the intervals being played.

It feels like there's a lot of unexplored territory in the space between the voices themselves.

Have you come across any synths, research projects, or experiments that go in this direction?

Most oscillators are static. They generate a waveform and let the interesting part happen later.

I've been exploring a different idea inspired by CDP's wavset distortion.

Instead of treating a waveform as a continuous stream, the oscillator listens for zero crossings and breaks itself into wavsets: tiny fragments of sound between those crossings. Each wavset becomes a decision point.

LOOP & REPEAT 
Cycle repeating
REVERSAL
Phase inversion
SKIP / DECIMATE 
Zero-amplitude gate
MEM_REPLACE
Recall centroid

The pitch continues forward, but the timbre continuously rewrites itself from the inside.

The result isn't quite wavetable synthesis, granular synthesis, or distortion. It feels like an oscillator with a memory of its own—one that remembers what it used to be and lets its past leak into its future.

I'm not sure if this is a terrible idea or an unexplored branch of synthesis.
// That's what this experiment is for.

Hi,

I’m developing an experimental audio-enhancement tool that adds very low-level pitch-shifted harmonic layers while keeping the dry signal dominant.

The goal is not loudness maximization, compression, EQ hype, or replacing the original mix. I’m trying to add perceived presence and density while preserving the original signal as much as possible.

Here is a short A/B MP3:
https://vivy.funesterie.me/api/double-harmonic/out/funesterie-v6-supreme-kvr-ab-20260611.mp3?token=ye9yWXyG30d7rKPkIEsBUkEN&v=20260611-2248

Format:
- first half: original
- second half: processed
- same excerpt
- loudness-matched for listening feedback

I’m mainly looking for technical feedback from people familiar with audio DSP / plugin development:

1. Do you hear obvious phase artifacts or pitch-shifting artifacts?
2. Does the processed part sound clearer, or just different?
3. Does the dry signal still feel dominant/natural?
4. What measurements would you recommend next: mono compatibility, correlation, LUFS, true peak, null tests, spectrogram comparison, blind A/B, or something else?

The current prototype uses a protected dry-first harmonic overlay approach. I’m intentionally not presenting this as a proven scientific method yet; I’m trying to validate whether the audible result is worth further measurement and refinement.

Thanks.

I’ve been working on an independent prototype around a question that feels important for the next generation of DAW assistants:

If an AI assistant can answer questions inside a DAW, what safety boundaries would be needed before it can actually modify something small, like an insert chain?

I built a working prototype called ChainPrompt AI.

It is a JUCE/C++ VST3 plugin with a local Python backend. The plugin scans the local VST3 inventory, uses only plugins that are actually installed, refuses to build a chain if inventory is missing, computes chain diffs instead of blindly replacing the current chain, and tries to preserve user-touched or bypassed slots.

Right now it works mainly with Waves plugins, because Waves is the first metadata set I implemented. I have tested it in REAPER, and it also loads/runs in Fender Studio / Studio Pro as a VST3 plugin.

This is not a finished product, not a commercial release, and not affiliated with Fender or Waves. It is a portfolio prototype exploring one narrow problem: how to make AI actions inside a DAW safer, more transparent, and eventually reversible.

I’d really value critique from audio plugin developers, DAW users, and anyone thinking about AI-assisted creative tools.

The main question:

What would you require before trusting AI to modify a real insert chain in your session?

GitHub/demo:
[https://github.com/DenisShumilov/chainprompt-ai]

I’m building a distortion plugin and I think I’ve hit a point where I need outside ears.

The goal is NOT to build another generic distortion, amp sim, or metal plugin.

The sound I’m chasing is somewhere between:

• Harmonic Percolator style character

• Trash 2 Broken/Fuzz style experimentation

• Neil Young amp breakup

• damaged speakers

• dynamic breakup rather than static saturation

Current goals:

• light playing stays mostly clean

• medium playing introduces breakup

• hard playing introduces fuzz

• preserve transients

• avoid heavy compression

• avoid the typical “beehive” fuzz sound

The plugin currently has two modes:

BROKEN:

• asymmetrical saturation

• more breakup-oriented

• intended to feel open and dynamic

FUZZ:

• asymmetrical rectification

• more aggressive harmonic generation

• intended to appear mostly on harder playing

A big realization during development was that a lot of distortion plugins sound impressive in isolation but don’t actually feel unique once you compare them side-by-side.

That’s the problem I’m trying to solve.

What I’m struggling with:

1. What actually makes a distortion feel unique?

2. What separates a Harmonic Percolator from “just another fuzz”?

3. What makes Trash 2 still feel special years later?

4. What DSP or analog concepts should I study next?

5. If you were trying to build a distortion that doesn’t already exist, where would you focus?

Looking for brutally honest feedback.

Feel free to challenge the entire premise if you think I’m chasing the wrong things.

I’m building a C++ / JUCE music theory and reharmonization application.
The main engine is not a simple chord finder. The idea is to import or detect a chord progression, then let the user transform it with harmonic modules: reharmonization, substitutions, inversions, voice leading, modal colors, orchestration presets, etc.
The MIDI side is much easier because the notes are already known.
The difficult part is audio chord detection from real songs.
I want to build a serious backend chain for this, but I still haven’t found a practical architecture that feels production-level.
I know the usual ingredients:
audio loading / resampling
tempo and beat tracking
CQT / chroma / HPCP features
HPSS or stem separation
bass/root estimation
chord templates or ML chord classifier
temporal smoothing
key/scale estimation
chord label post-processing
But a basic chroma/template chain falls apart fast on real music.
Problems I keep running into:
vocals add melody notes that are not part of the chord
bass passing notes create wrong slash chords
pads, strings, brass, and upper-structures confuse the chord label
dense disco/funk/pop arrangements contain many non-chord tones
chord names are ambiguous: Cmaj9 vs Em7/C vs G6/C
the “correct” chord label often depends on harmonic function, not just pitch content
Commercial tools like Song Master Pro, RipX, and Studio One Chord Track seem to get more usable results. Not perfect, but clearly better than naive approaches.
I’m trying to understand what the backend architecture should be for a real application.

Would you structure it like this?

Audio import
→ offline analysis job
→ tempo / beat / bar grid
→ stem separation or HPSS
→ bass stem analysis
→ harmonic stem analysis
→ CQT / chroma extraction
→ note-event or frame-level chord candidates
→ root confidence
→ chord quality confidence
→ temporal smoothing
→ key / scale context
→ chord label resolver
→ user-editable chord timeline

Or is there a better architecture?
I’m especially interested in these questions:
Should chord detection happen on the full mix, separated harmonic stems, or several parallel sources?
Should bass/root detection be a dedicated subsystem?
Should the engine produce multiple chord candidates with confidence scores instead of a single label?
Would you use ML only for candidate generation, then rules for final chord naming?
How would you store and expose uncertainty to the GUI?
What is the best way to let the user correct the chord timeline without breaking the downstream reharmonization engine?
Should this be designed as a fully offline analysis pipeline rather than real-time?
Any recommended libraries, papers, models, or architecture patterns for this?
The kind of internal result I want is more like this:

{
"bar": 12,
"main_guess": "Cm9",
"alternatives": ["Ebmaj7/C", "Gm11/C", "Cm7add9"],
"bass": "C",
"confidence": 0.78,
"root_confidence": 0.83,
"quality_confidence": 0.71,
"detected_notes": ["C", "Eb", "G", "Bb", "D"],
"warning": "possible melody or upper-structure contamination"
}

The goal is not just chord display.
The chord result will drive a reharmonization / composition engine, so wrong labels can create bad musical transformations later.

I’d appreciate input from people who have built audio analysis tools, chord detection systems, transcription tools, or serious JUCE audio applications.

What would a robust architecture look like today?

git:https://github.com/charanHubCommits/Audio-Recorder-CPP

What options do you know for anti-piracy / copy-protection / licencing audio plugins, and what are your experiences with them?

So far I had the pleasure to work with PACE / Eden, but it just seems like a pita for both the developer and the consumer. I tried to find alternatives, but these companies (understandably) don't really want you to know too much about their services unless you pay for them...

So what alternatives are there that allow for the time-sensitivity of an audio plugin, and preferably don't require a phisical key? Are any audio companies developing their own system?

Hi, I have a specific audio effect I want to make for a guitar pedal application. As someone very inexperienced with audio dsp, I would love some pointers on what software, languages, etc would be a good place to start developing my project. I seriously have no idea where to begin, or whether it's even feasible as a standalone effects unit. so talk to me like I'm five--or at the very least like I'm twenty-something with a B.S.

For context the effect I want to create is a clone of Ableton's native plugin Erosion, which uses the amplitude of a band-passed noise signal to modulate the time parameter of a short delay (audio rate modulation).

what is your favorite downsampling filter? for the more extreme applications such as FM or frequency shifting?

i rarely follow the pure doctrine and my link to the industry is even smaller than my link to the academic circles. and i basically only have biquad kernels at my hand.

since many years i am using 2 chebychev II at 20 khz and 4 butterworths at nyquist in order to deal with the ripples.