Skip to main content
VoiceMark’s speaker verification was tested against two adversarial conditions using the ECAPA-TDNN pipeline (spkrec-ecapa-voxceleb, 192-dim) with cosine similarity.

Methodology

  • Genuine pairs: Three recordings of the target speaker (enrolled + two verify samples)
  • Impostor condition A — human: 12 recordings from different speakers from the same audio corpus
  • Impostor condition B — pre-existing AI: 13 recordings from pre-existing synthetic/cloned voices (non-IVC)
  • Metric: Equal Error Rate (EER) — the threshold where FAR (false accept rate) equals FRR (false reject rate)

Results

Genuine speaker scores and impostor scores show no overlap at the operating threshold, with a wide separation margin between the two distributions.

Configuration

  • Similarity metric: Cosine similarity on speaker embeddings
  • Threshold: Tuned per deployment environment
  • Liveness: f0 variation analysis (not applied in this test run)

Upcoming conditions

The following conditions are planned for future test runs:
  • XTTS-v2 open-source clone (local, $0 cost) — IVC using the target speaker’s enrollment audio
  • Hesitation signature analysis — comparing disfluency/pause patterns in real speech vs TTS output