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Let song agents iterate on rendered features

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Meta Vens 2026-05-31 13:09:57 +01:00
commit 4b40d12816
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docs/audio-doctrine.md
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@ -320,11 +320,19 @@ Useful metrics:
Song-scene parity targets must publish target evidence before candidate golf:
log-mel spectrogram CSV, per-band statistics, first and second derivative
summaries, RMS envelope, and envelope autocorrelation. Those artifacts are not
loose side files only; scoring writes them as typed song challenge evidence
records in the `.cc` CultCache/CultMesh store and references them from each
trial result. Qdrant/Ollama retrieval may derive vectors from those records, but
the `.cc` records remain truth.
summaries, RMS envelope, envelope autocorrelation, and whitened spectral
autocorrelation over band-normalized log-mel flux. Those artifacts are not loose
side files only; scoring writes them as typed song challenge evidence records in
the `.cc` CultCache/CultMesh store and references them from each trial result.
Qdrant/Ollama retrieval may derive vectors from those records, but the `.cc`
records remain truth.
Song-scene agents should iterate like a tiny studio. Render the candidate,
extract the same features from the Faust output, compare target and candidate
band motion, envelope autocorrelation, whitened spectral autocorrelation,
loudness, centroid, and instrument-role metrics, then move sources, filters,
gates, patterns, and gains. A one-shot patch is sample data; a five-attempt
revision trace is curriculum.
Noise is not a scene by itself. Background air, dust, codec grit, tape, vinyl,
and room color need a role owner that shapes spectrum and time. Prefer