- 128-sample cpal audio buffers (~2.7ms at 48kHz) - Single-cycle pitch detection - 2-frame McLeod pitch voting for confirmation - Entire DSP pipeline is Rust, pre-allocated ring buffers with minimal heap pressure
The e2e from pluck to MIDI "note-on" signal, is under 10ms on an M-series Mac. Hardware matters for sure so an audio interface with low-latency drivers (I use an Audient iD14) helped a lot. The web version (app.contrapunk.com) adds AudioWorklet latency on top, so the native Mac app is noticeably tighter. I am still working on figuring out how to have lesser noise and pitch jitter in the final output. Also this works really well for higher notes, bass not so much right now. Still need to figure out how to handle harmonics better. I have created this issue for you for now, let me know if you would like to add anything else to this as well. https://github.com/contrapunk-audio/contrapunk/issues/6.
I've got a few thoughts for features, if you're open to them:
1. Ability to specify where your "played" voice resides in the voicing: As the bass note, as an inner voice, or as the top line.
2. Options for first species, second species, third, florid, etc counterpoint for each of the generated voices. Ex: You play a single note and the upper voice plays two notes for every one of yours, etc, etc.
3. If you want to get real fancy, make the generated voices perform a canon of your played notes.
How are you finding rust for audio development? I have a background in pro audio, and both for the audio and GPU render threads, I used a lot of arena allocators and ring buffers. Do you find yourself fighting with rust's strict semantics?
FYI in this phrase: "AI is not going to kill music till people keep playing music together."
The "till" (until) kind of inverts what I think is the intended meaning.
A better replacement would be "as long as".
macOS DMG: https://github.com/contrapunk-audio/contrapunk/releases/tag/...
Source: https://github.com/contrapunk-audio/contrapunk (do open any issues if you have any)
Would love feedback on the DSP approach and the harmony algorithms. I am also looking at training a ML model for better realtime guitar to midi detection. I believe that will take some time.