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comparison: drop 24 kHz anchor (>=44k class only)

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@@ -52,7 +52,6 @@ the only one here whose token stream an autoregressive LLM/TTS model can practic
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  |---|--:|--:|--:|--:|--:|--:|--:|--:|
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  | ground truth | β€” | β€” | β€” | β€” | 2.822 | β€” | 0.00244 | 8263 |
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  | nvidia nemo44k | 44.1k | ~86 | RVQ (many) | ~6–9 kbps | **2.903** | 0.379 | 0.00196 | 8372 |
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- | neucodec (24k anchor) | 24k | 50 | 1 | ~0.8 kbps | 2.848 | 0.706 | 0.00005 | 6214 |
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  | **WideCodec (ours, gs-2.0M)** | 44.1k | **50** | **1** | **~0.8 kbps** | **2.788** | 0.571 | 0.00223 | 9011 |
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  | dac | 44.1k | 86 | 9 | ~8 kbps | 2.672 | **0.341** | 0.00156 | 8185 |
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  | snac44k | 44.1k | multi-scale | 3–4 | ~2.6 kbps | 2.340 | 0.493 | 0.00158 | 8402 |
@@ -62,7 +61,7 @@ the only one here whose token stream an autoregressive LLM/TTS model can practic
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  num_quantizers=1` β†’ 8Β·logβ‚‚4 = **16 bits/frame** Γ— 50 frames/s = **800 bps = 0.8 kbps**
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  (vs DAC's 9 codebooks Γ— 10 bits Γ— 86 fps β‰ˆ 8 kbps).
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- The **WideCodec row is the final gs-2.0M checkpoint** (9,291-clip set). At ~0.8 kbps / 1 codebook it **beats DAC on naturalness** (UTMOSv2 2.79 vs 2.67) using ~10x fewer bits, and unlike the 24 kHz anchor it carries real high-band content (rolloff 9.0 kHz; HF energy ~91% of GT vs the anchor's ~0). On reference-based metrics it beats the 24 kHz anchor on all six (PESQ 2.08, ESTOI 0.79, LSD-HF 0.96 vs 2.26, ECAPA-sim 0.87). Full report:
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  [evaluation/REPORT_44k_class_codecs.md](https://github.com/Scicom-AI-Enterprise-Organization/WideCodec/blob/main/evaluation/REPORT_44k_class_codecs.md).
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  ## Training stages / which revision to pull
 
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  |---|--:|--:|--:|--:|--:|--:|--:|--:|
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  | ground truth | β€” | β€” | β€” | β€” | 2.822 | β€” | 0.00244 | 8263 |
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  | nvidia nemo44k | 44.1k | ~86 | RVQ (many) | ~6–9 kbps | **2.903** | 0.379 | 0.00196 | 8372 |
 
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  | **WideCodec (ours, gs-2.0M)** | 44.1k | **50** | **1** | **~0.8 kbps** | **2.788** | 0.571 | 0.00223 | 9011 |
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  | dac | 44.1k | 86 | 9 | ~8 kbps | 2.672 | **0.341** | 0.00156 | 8185 |
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  | snac44k | 44.1k | multi-scale | 3–4 | ~2.6 kbps | 2.340 | 0.493 | 0.00158 | 8402 |
 
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  num_quantizers=1` β†’ 8Β·logβ‚‚4 = **16 bits/frame** Γ— 50 frames/s = **800 bps = 0.8 kbps**
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  (vs DAC's 9 codebooks Γ— 10 bits Γ— 86 fps β‰ˆ 8 kbps).
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+ The **WideCodec row is the final gs-2.0M checkpoint** (9,291-clip set). At ~0.8 kbps / 1 codebook it **beats DAC on naturalness** (UTMOSv2 2.79 vs 2.67) using ~10x fewer bits, and lands within ~0.12 of NeMo's ~6-9 kbps RVQ. It carries genuine high-band content (rolloff 9.0 kHz; HF energy ~91% of ground truth), and its reference-based panel (PESQ 2.08, ESTOI 0.79, LSD-HF 0.96, ECAPA-sim 0.87) trades in-band fidelity for a ~10x bitrate advantage over the RVQ codecs. Full report:
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  [evaluation/REPORT_44k_class_codecs.md](https://github.com/Scicom-AI-Enterprise-Organization/WideCodec/blob/main/evaluation/REPORT_44k_class_codecs.md).
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  ## Training stages / which revision to pull