[
  {
    "name": "9sys_+flux+f0",
    "experiment_id": 18,
    "lock_date": "2026-02-18",
    "overall_eer": 4.44,
    "mean_attack_eer": 3.09,
    "worst_eer": 14.63,
    "worst_attack": "A18",
    "per_attack_eer": {
      "A07": 1.11,
      "A08": 0.34,
      "A09": 0.02,
      "A10": 2.3,
      "A11": 0.42,
      "A12": 1.27,
      "A13": 0.14,
      "A14": 5.55,
      "A15": 2.36,
      "A16": 1.17,
      "A17": 11.48,
      "A18": 14.63,
      "A19": 0.38
    },
    "architecture": "9 classifiers (3 codecs x 3 core features: LFCC/CQCC/MGDCC). Each classifier's input = core_feature(360-dim) + spectral_flux(12-dim) + f0_trajectory(24-dim) = 396-dim. Per-system StandardScaler, LogisticRegression(C=0.1, solver=lbfgs, max_iter=2000, seed=42). Min-max score normalization per system, avg_score fusion across 9 systems.",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory"
    ],
    "baseline_role": "canonical",
    "canonical": true
  },
  {
    "name": "mega_all5",
    "experiment_id": 18,
    "lock_date": "2026-02-18",
    "overall_eer": 4.7,
    "mean_attack_eer": 3.04,
    "worst_eer": 18.31,
    "worst_attack": "A14",
    "per_attack_eer": {
      "A07": 0.78,
      "A08": 0.26,
      "A09": 0.0,
      "A10": 1.85,
      "A11": 0.32,
      "A12": 0.95,
      "A13": 0.09,
      "A14": 18.31,
      "A15": 1.99,
      "A16": 0.8,
      "A17": 5.73,
      "A18": 8.06,
      "A19": 0.42
    },
    "architecture": "3 mega-classifiers (1 per codec). Each classifier's input = LFCC(360) + CQCC(360) + MGDCC(360) + spectral_flux(12) + f0_trajectory(24) = 1116-dim. Per-codec StandardScaler, LogisticRegression(C=0.1, solver=lbfgs, max_iter=2000, seed=42). Min-max score normalization per codec, avg_score fusion across 3 codecs.",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory"
    ],
    "baseline_role": "canonical",
    "canonical": true
  },
  {
    "name": "delta_pareto_9sys",
    "experiment_id": 20,
    "lock_date": "2026-02-19",
    "overall_eer": 4.15,
    "mean_attack_eer": 2.76,
    "worst_eer": 12.33,
    "worst_attack": "A17",
    "per_attack_eer": {
      "A07": 0.68,
      "A08": 0.22,
      "A09": 0.01,
      "A10": 2.9,
      "A11": 0.29,
      "A12": 0.82,
      "A13": 0.08,
      "A14": 3.7,
      "A15": 2.3,
      "A16": 0.78,
      "A17": 12.33,
      "A18": 8.4,
      "A19": 0.28
    },
    "architecture": "9 classifiers (3 codecs x 3 core features: LFCC/CQCC/MGDCC). Each classifier's input = delta(static+\u0394+\u0394\u0394, 1080-dim) + spectral_flux(12-dim) + f0_trajectory(24-dim) = 1116-dim. Per-system StandardScaler, LogisticRegression(C=0.1, solver=lbfgs, max_iter=2000, seed=42). Min-max score normalization per system, Pareto-weighted avg_score fusion (wideband=1.5, g711_ulaw=1.5, amr_nb=1.0).",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory"
    ],
    "baseline_role": "canonical",
    "canonical": true
  },
  {
    "name": "exp37b_blend_1500d",
    "experiment_id": 37,
    "lock_date": "2026-02-22",
    "overall_eer": 3.13,
    "mean_attack_eer": 1.91,
    "worst_eer": 9.88,
    "worst_attack": "A17",
    "per_attack_eer": {
      "A07": 0.56,
      "A08": 0.7,
      "A09": 0.0,
      "A10": 1.45,
      "A11": 0.0,
      "A12": 0.5,
      "A13": 0.0,
      "A14": 1.78,
      "A15": 1.82,
      "A16": 0.7,
      "A17": 9.88,
      "A18": 6.05,
      "A19": 1.45
    },
    "architecture": "27 classifiers (3 codecs x 3 core features x 3 classifier types). Each classifier's input = delta(static+\u0394+\u0394\u0394, 1080-dim) + spectral_flux(12-dim) + f0_trajectory(24-dim) + IFCC_delta(360-dim) + HF/LF_comod(24-dim) = 1500-dim. Three classifier types per (codec, core_feature): (1) Standard LR(C=0.1, solver=lbfgs, max_iter=2000, seed=42); (2) OHEM-LR: two-pass LR with loss-based sample weights from pass-1 (cap=5.0); (3) Shallow LGBM(n_estimators=200, max_depth=4, learning_rate=0.05, subsample=0.8, colsample_bytree=0.8, seed=42). Per-system StandardScaler, min-max score normalization. Pareto-weighted avg_score per classifier type (wideband=1.5, g711_ulaw=1.5, amr_nb=1.0). 3-component blend: score = 0.66 \u00d7 OHEM + 0.04 \u00d7 LGBM + 0.30 \u00d7 LR.",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory",
      "ifcc",
      "hf_lf_comod"
    ],
    "baseline_role": "canonical",
    "canonical": true
  },
  {
    "name": "exp40_cqcc_blend",
    "experiment_id": 40,
    "lock_date": "2026-02-24",
    "overall_eer": 3.35,
    "mean_attack_eer": 2.4,
    "worst_eer": 7.53,
    "worst_attack": "A17",
    "per_attack_eer": {
      "A07": 1.46,
      "A08": 1.47,
      "A09": 0.01,
      "A10": 2.45,
      "A11": 0.24,
      "A12": 0.1,
      "A13": 0.01,
      "A14": 2.41,
      "A15": 3.06,
      "A16": 1.37,
      "A17": 7.53,
      "A18": 6.62,
      "A19": 4.48
    },
    "architecture": "27 classifiers (3 codecs x 3 core features x 3 classifier types). Each classifier's input = delta(static+\u0394+\u0394\u0394, 1080-dim) + spectral_flux(12-dim) + f0_trajectory(24-dim) + IFCC_delta(360-dim) + HF/LF_comod(24-dim) = 1500-dim. Three classifier types per (codec, core_feature): (1) Standard LR(C=0.1, solver=lbfgs, max_iter=2000, seed=42); (2) OHEM-LR: two-pass LR with loss-based sample weights from pass-1 (cap=5.0); (3) Shallow LGBM(n_estimators=200, max_depth=4, learning_rate=0.05, subsample=0.8, colsample_bytree=0.8, seed=42). Per-system StandardScaler, min-max score normalization. CQCC-weighted Pareto fusion (CQCC=1.5, LFCC=0.75, MGDCC=0.25) with codec weights (wideband=1.5, g711_ulaw=1.5, amr_nb=1.0). 3-component blend: score = 0.60 \u00d7 OHEM + 0.16 \u00d7 LGBM + 0.24 \u00d7 LR.",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory",
      "ifcc",
      "hf_lf_comod"
    ],
    "baseline_role": "canonical",
    "canonical": true
  },
  {
    "name": "exp44_scc_cqcc_blend",
    "experiment_id": 44,
    "lock_date": "2026-02-26",
    "overall_eer": 3.48,
    "mean_attack_eer": 2.54,
    "worst_eer": 7.83,
    "worst_attack": "A17",
    "per_attack_eer": {
      "A07": 2.15,
      "A08": 1.88,
      "A09": 0.02,
      "A10": 2.62,
      "A11": 0.13,
      "A12": 0.14,
      "A13": 0.14,
      "A14": 2.65,
      "A15": 2.9,
      "A16": 1.85,
      "A17": 7.83,
      "A18": 5.25,
      "A19": 5.5
    },
    "architecture": "27 classifiers (3 codecs x 3 core features x 3 classifier types). Each classifier's input = delta(static+\u0394+\u0394\u0394, 1080-dim) + spectral_flux(12-dim) + f0_trajectory(24-dim) + IFCC_delta(360-dim) + HF/LF_comod(24-dim) + SCC_delta(360-dim) = 1860-dim. SCC = wavelet scattering transform (J=2, Q=10, order=2) \u2192 log \u2192 DCT (20 coeffs). Three classifier types per (codec, core_feature): (1) Standard LR(C=0.1, solver=lbfgs, max_iter=2000, seed=42); (2) OHEM-LR: two-pass LR with loss-based sample weights from pass-1 (cap=5.0); (3) Shallow LGBM(n_estimators=200, max_depth=4, learning_rate=0.05, subsample=0.8, colsample_bytree=0.8, seed=42). Per-system StandardScaler, Platt-calibrated scores (LogisticRegression on 1D). CQCC-weighted Pareto fusion (CQCC=2.5, LFCC=0.5, MGDCC=0.25, strong-B) with codec weights (wideband=1.5, g711_ulaw=1.5, amr_nb=1.0). 3-component blend: score = 0.47 \u00d7 OHEM + 0.15 \u00d7 LGBM + 0.38 \u00d7 LR.",
    "codecs": [
      "wideband",
      "g711_ulaw",
      "amr_nb"
    ],
    "feature_types": [
      "lfcc",
      "cqcc",
      "mgdcc",
      "spectral_flux",
      "f0_trajectory",
      "ifcc",
      "hf_lf_comod",
      "scc_delta"
    ],
    "baseline_role": "canonical",
    "canonical": true
  }
]