README.md

metadata

license: apache-2.0
task_categories:
  - audio-classification
tags:
  - anti-spoofing
  - voice-fraud-detection
  - asvspoof
  - codec-aware
  - calibration-baselines
pretty_name: Sonotheia Voice Fraud Detection Baselines
size_categories:
  - n<1K

Sonotheia Calibration Baselines

Frozen calibration baselines from the Sonotheia voice fraud detection platform.

Overview

These baselines represent Sonotheia's interpretable, physics-based approach to voice spoofing detection evaluated on ASVspoof 2019 LA (eval partition, attacks A07–A19). No neural networks — linear classifiers on hand-crafted acoustic features with codec-aware calibration.

Baseline	Overall EER	Mean Attack EER	Worst EER	Worst Attack	Role
9sys_+flux+f0	4.44%	3.09%	14.63%	A18	canonical
mega_all5	4.70%	3.04%	18.31%	A14	canonical
delta_pareto_9sys	4.15%	2.76%	12.33%	A17	canonical
exp37b_blend_1500d	3.13%	1.91%	9.88%	A17	canonical
exp40_cqcc_blend	3.35%	2.40%	7.53%	A17	canonical
exp44_scc_cqcc_blend	3.48%	2.54%	7.83%	A17	canonical

Best Configuration: exp37b_blend_1500d

• Overall EER: 3.13% on ASVspoof 2019 LA eval set
• 27 classifiers (3 codecs x 3 features x 3 classifier types)
• 1500-dim feature vector per classifier
• Pareto-weighted codec fusion + 3-component blend (OHEM-LR + LGBM + LR)

Per-Attack EER Breakdown

Attack	9sys_+flux+f0	mega_all5	delta_pareto_9sys	exp37b_blend_1500d	exp40_cqcc_blend	exp44_scc_cqcc_blend
A07	1.11%	0.78%	0.68%	0.56%	1.46%	2.15%
A08	0.34%	0.26%	0.22%	0.70%	1.47%	1.88%
A09	0.02%	0.00%	0.01%	0.00%	0.01%	0.02%
A10	2.30%	1.85%	2.90%	1.45%	2.45%	2.62%
A11	0.42%	0.32%	0.29%	0.00%	0.24%	0.13%
A12	1.27%	0.95%	0.82%	0.50%	0.10%	0.14%
A13	0.14%	0.09%	0.08%	0.00%	0.01%	0.14%
A14	5.55%	18.31%	3.70%	1.78%	2.41%	2.65%
A15	2.36%	1.99%	2.30%	1.82%	3.06%	2.90%
A16	1.17%	0.80%	0.78%	0.70%	1.37%	1.85%
A17	11.48%	5.73%	12.33%	9.88%	7.53%	7.83%
A18	14.63%	8.06%	8.40%	6.05%	6.62%	5.25%
A19	0.38%	0.42%	0.28%	1.45%	4.48%	5.50%

Codec Conditions

All baselines evaluate across three codec conditions:

• wideband: Clean 16kHz (no codec)
• g711_ulaw: G.711 mu-law (PSTN telephony)
• amr_nb: AMR-NB (mobile telephony)

Files

• baselines.json — Full structured data with architectures
• baselines.csv — Flat CSV (one row per baseline x attack) for analysis

Citation

If you use these baselines for comparison, please cite:

Sonotheia: Interpretable Voice Fraud Detection with Codec-Aware Calibration
https://sonotheia.ai

License

Apache-2.0