VIPBench: A Human-Aligned Benchmark for Voice Identity Perception in the Age of Voice Cloning
Read the original on arXiv AI →VIPBench is a new benchmark that measures how humans perceive voice identity, using 124,876 same-or-different judgments from 1,290 listeners on 9,800 recording pairs involving real voices, voice clones, and morphed voices of 100 public figures. It defines four tasks to evaluate how well speaker‑representation models align with human judgments, including predicting majority responses and assessing similarity across real and synthetic recordings. Eleven publicly available speech models were evaluated, showing that listeners often misidentify cloned voices and that no model reaches the noise ceiling, with the best explaining only 61% of the explainable variance.
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