feat: add SelVA HF Smoother and Spectral Matcher preprocessing nodes

Two ComfyUI nodes to reduce domain mismatch between custom training audio
and the MMAudio VAE's expected spectral distribution:

SelvaHfSmoother: blends a low-pass filtered copy (biquad) with the original
at a configurable cutoff and blend ratio. Attenuates extreme HF content that
BigVGANv2 handles poorly. RMS-preserving.

SelvaSpectralMatcher: computes the log-mel energy profile of the clip,
compares it per-band to the VAE's normalization means (DATA_MEAN_80D/128D),
and applies a smooth STFT-domain gain correction to match the codec's training
distribution. Configurable strength and max_gain_db clamp. RMS-preserving.

Recommended workflow: SpectralMatcher → HfSmoother → feature extraction.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/__init__.py

@@ -12,6 +12,8 @@ _NODES = {
     "SelvaSkipExperiment":   (".selva_skip_experiment",   "SelvaSkipExperiment",   "SelVA Skip Experiment"),
     "SelvaLoraEvaluator":    (".selva_lora_evaluator",    "SelvaLoraEvaluator",    "SelVA LoRA Evaluator"),
     "SelvaVaeRoundtrip":     (".selva_vae_roundtrip",     "SelvaVaeRoundtrip",     "SelVA VAE Roundtrip"),
+    "SelvaHfSmoother":       (".selva_audio_preprocessors", "SelvaHfSmoother",       "SelVA HF Smoother"),
+    "SelvaSpectralMatcher":  (".selva_audio_preprocessors", "SelvaSpectralMatcher",  "SelVA Spectral Matcher"),
 }
 
 for key, (module_path, class_name, display_name) in _NODES.items():