cab-modeling

Partitioned FFT convolution enables real-time guitar cabinet modeling with low latency. It splits the impulse response into blocks, ensuring efficient processing for live rigs and zero-latency monitoring.

Neural interpolation for cabinet impulse responses approximates tone variations between mic positions and room sizes. It allows programmable morphing of guitar tone parameters in real time without loading multiple IR files.

JUCE supports real-time audio processing for cabinet modeling. This Skill implements deterministic IR synthesis and FFT-based convolution within a JUCE-based audio processor to handle sample-rate matching and live workflows.

Minimum-phase impulse responses enable zero-latency monitoring by avoiding pre-ringing artifacts. This Skill supports minimum-phase options alongside stereo IRs for direct, real-time tone shaping in live environments.

Yes, you can morph mic positions in a guitar cabinet impulse response. Neural cabinet interpolation allows you to dial in tone by morphing neural mic-position parameters in real time from a loaded IR.

FFT-based convolution for audio DSP can introduce latency compared to direct convolution. Partitioned convolution mitigates this by processing smaller blocks, making it suitable for real-time cabinet modeling without noticeable delay.