Speaker Identification

92^%

vs. HUMAN BASELINE = 100

SolvedConf · High

Scoring rubric

0–20

Early research

20–40

Narrow benchmark competence

40–60

Strong benchmark · reliability gaps

60–80

Human-competitive in common scenarios

80–100

Comparable to typical skilled adult

100+

Reliably exceeds typical human baseline

Trend · Last 12 months

12mo ago —%

6mo ago —%

Today —%

Δ 12mo +0

Human baseline

Distinguish known speakers from short clips in quiet conditions.

Human frontier

Robust speaker verification under adversarial deepfake and noisy conditions.

What works

Voice biometrics in production systems; VoxCeleb verification at low error rates.

Key gaps

Adversarial voice cloning; cross-language speaker verification.

1 source

Technology	Quality	Source	Score vs. baseline	Score
Whisper Large v3	independent	paperswithcode.com/sota/speaker-verification-on-voxceleb1		94%