# Speaker Verification

Deployment generalization for speaker verification now has a shared public evaluation: a fixed core organizes 16 public sources into 26 trial sets and 11 scenario groups with 9,150,366 verification trials, frozen target/non-target keys, and an online leaderboard that reports trial-set breakdowns, scenario-group metrics, and macro averages. Across 18 public checkpoints, systems with similar macro EER show different scenario profiles, strength in one scenario does not guarantee strength in another, and trial sets within the same scenario group still expose source and protocol gaps.

Deployment generalization for speaker verification now has a shared public evaluation: a fixed core organizes 16 public sources into 26 trial sets and 11 scenario groups with 9,150,366 verification trials, frozen target/non-target keys, and an online leaderboard that reports trial-set breakdowns, scenario-group metrics, and macro averages. Across 18 public checkpoints, systems with similar macro EER show different scenario profiles, strength in one scenario does not guarantee strength in another, and trial sets within the same scenario group still expose source and protocol gaps.

The work trains 15 masked-diffusion codec TTS models (19-133M parameters, 3 seeds) on 2,000 hours of speech and sweeps refinement steps T in [1,16] at inference, measuring zero-shot synthesis on 174 held-out speakers via ASR word error rate and speaker verification; refinement closes 86.2% of the intelligibility range but only 46.4% of the identity range (a 1.86x asymmetry), Best-of-K search recovers identity with 64.6-79.0% win rates across four independent encoders, a separable B(d)B(T) model fits significantly better than substitution models (Delta AICc=+69.3), and 62% of the remaining identity deficit lies in the codec rather than the generator.

The work trains 15 masked-diffusion codec TTS models (19-133M parameters, 3 seeds) on 2,000 hours of speech and sweeps refinement steps T in [1,16] at inference, measuring zero-shot synthesis on 174 held-out speakers via ASR word error rate and speaker verification; refinement closes 86.2% of the intelligibility range but only 46.4% of the identity range (a 1.86x asymmetry), Best-of-K search recovers identity with 64.6-79.0% win rates across four independent encoders, a separable B(d)B(T) model fits significantly better than substitution models (Delta AICc=+69.3), and 62% of the remaining identity deficit lies in the codec rather than the generator.