I’ve been working on a long-running personal DSP experiment that started from a simple observation: most real-world listening happens on constrained systems — phone speakers, budget earbuds, car audio, Bluetooth, and heavily compressed streams. In that environment, “accurate” or “flat” processing often doesn’t survive contact with reality.
Instead of optimizing for frequency response, I tried optimizing for perceptual survival under constraints. The system is built around a few principles:
• Virtual pitch / harmonic reconstruction to preserve perceived low-end on small transducers • Targeted removal of low-mid intermodulation zones that create perceived “mud” on cheap hardware • A biologically-informed notch around the ear-canal resonance region to reduce fatigue at higher listening levels • Minimum-phase, high-headroom internal processing to preserve transient coherence • Treating codecs, OS mixers, and streaming artifacts as first-class constraints, not edge cases
The interesting outcome (at least to me) is that this kind of pipeline seems to hold up better across:
• Low-bitrate or aggressively compressed streams • Weak or highly non-linear speakers • Long listening sessions where fatigue usually becomes a problem
It’s not trying to be “reference accurate.” It’s trying to be perceptually stable across hostile playback conditions.
I’m not sharing coefficients or presets — this is more about the architecture and design philosophy than any specific tuning. I’m curious how people here think about:
• Perceptual DSP vs measurement-driven pipelines • Designing audio systems around human hearing limits instead of ideal transducers • Whether codec- and hardware-aware processing should live at the OS / SoC / app layer • Where this kind of approach would break in real products
I’d especially love input from folks working on audio DSP, mobile SoCs, streaming, codecs, OS audio stacks, or playback hardware. What would you challenge here? What would you try instead?
This is a research playground for me, but I’m very interested in the engineering discussion.