---
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](https://sonotheia.ai) 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