AI RESEARCH
AnimeScore: A Preference-Based Dataset and Framework for Evaluating Anime-Like Speech Style
arXiv CS.CL
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ArXi:2603.11482v1 Announce Type: cross 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.