code-v107: SNN Sound Companion learning and memory

Sound Companion now learns labeled microphone sounds with an SNN. Both input synapses and the class readout train, older taught examples are replayed for retention, and trained parameters reload without fitting. The SNN chooses action labels; a separate example-support guard can reject them. The previous matcher runs as a comparison control. Teaching, correction and forgetting run outside the Tk event loop.

Existing sound memory is imported while preserving the original file. Fresh test recordings score both backends without training or triggering actions.

Verification for source c306986c3f5035ccb2bd98fc0a195ee46b466c1b:

• 87 distinct affected checks verified: 77 unchanged non-window checks reused from an 86-test pass, plus all 10 final native-window checks after layout fixes. Exact receipts and source hashes are retained; this was not another combined 87-test run.
• Frozen comparison: each of three SNN seeds scored 48/48 after teaching four generated sound families and after reload. The matcher tied. The same 48 clips were reused across seeds; these are not microphone accuracy results.
• Mean software decision time, including scheduled controls: SNN plus guard 2.07 ms; matcher 0.81 ms. No SNN speed or energy advantage is claimed. Raw neural unknown choices still require the rejection guard.
• Independent aggregate verification checked 1,708 numeric assertions and rejected three corrupted reports. All 18 plotted values/denominators were checked.
• Physical microphone calibration, level delivery, clean shutdown and lock release were checked. Personal audio and learned parameter arrays are not included.

This pre-release also includes the microphone checkpoint and training-memory work committed since code-v106; its earlier negative findings remain in the saved reports. No full local suite or current-source full-CI acceptance is claimed, and remote CI was not awaited.

Run and teach sounds · Comparison and limitations · Verification evidence