(feat) Create per model/avatar/user calibration

[dfgHiatus]

Currently, the Babble App stores one calibration. This could be enhanced if calibrations could be stored per user AND avatar, with a default/fallback config per user.

These could then be loaded manually OR automatically when a user's avatar changes (say in VRChat via OSC). This could be represented by a tree dropdown selector, and be enabled/disabled like so:

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...

• [ ] Automatically apply per-avatar configuration

• User 1
  • Avatar A
  • Avatar B
  • ...
  • Default
• User 2
  • Avatar A
  • Avatar B
  • ...
  • Default

...

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With options to edit/delete entries as required.

[RamesTheGeneric]

Perhaps we can have a model "global" calibration like what we have now and have profile selectable "modifiers" that are applied on top of the global calibration. For example, there could be a second normalization someone can use to "boost" the output of a specific shape. Another example could be utilizing a curve for nonlinear shape activations.