Thank you for your thoughtful response—there’s much I appreciate in your observations, especially your recognition of the perceptual impact of the 200–250 Hz region. That masking effect is something I’ve encountered before, and it’s reassuring to hear it echoed from another listener with a keen ear.
You’re absolutely right that a 2 dB boost at 200 Hz is not revolutionary in itself, and that such adjustments can be found through conventional research or trial and error. But, for me, the value of AI here wasn’t in suggesting something novel—it was in helping me
converge on the most effective intervention with precision, restraint, and comparative speed..
To reiterate, the process involved:
- Parsing REW and GRADE data alongside subjective listening goals.
- Navigating GLM’s notch constraints and group architecture.
- Iterating through multiple candidate groups with documented feedback loops.
In the end, yes, the final group involved only three changes. But those changes were distilled from a much broader field of possibilities, and the AI helped me to avoid overcorrection, preserve linearity, and maintain tonal coherence. It wasn’t about chasing dramatic shifts—it was about refining the system’s response to better reflect my listening priorities (in a way that is more delicate/refined than what SCP offers).
As for the 90 Hz cut: I agree that 0.5 dB is subtle, but in my room it helped soften a low-end bloom that was perceptually distracting. The Q was broad enough to act as a gentle contour, not a surgical notch. And the 2800 Hz placeholder was a deliberate non-intervention—anchoring the notch architecture while preserving upper-mid neutrality.
Ultimately,, I found the AI a valuable companion—not for its novelty, but for its clarity, its ability to contextualize, and its support in arriving at a voicing that feels both personal and grounded.
Warm thanks again for engaging so thoughtfully.