AnimeScore: A Preference-Based Dataset and Framework for Evaluating Anime-Like Speech Style
Evaluating 'anime-like' voices currently relies on costly subjective judgments, yet no standardized objective metric exists. A key challenge is that anime-likeness, unlike naturalness, lacks a shared absolute scale, making conventional Mean Opinion Score (MOS) protocols unreliable. To address this gap, we propose AnimeScore, a preference-based framework for automatic anime-likeness evaluation via pairwise ranking. We collect 15,000 pairwise judgments from 187 evaluators with free-form descriptions, and acoustic analysis reveals that perceived anime-likeness is driven by controlled resonance shaping, prosodic continuity, and deliberate articulation rather than simple heuristics such as hig...
| Authors | Joonyong Park, Jerry Li |
|---|---|
| Primary category | cs.SD |
| Published | 12 March 2026 |
| Last updated at source | 9 June 2026 |
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