besimple-ai/vocal-affect-bench
VocalAffectBench VocalAffectBench is a test-only benchmark for evaluating whether AI audio models can identify expressed vocal emotion from raw audio. Paper: VocalAffectBench: Evaluating Vocal Emotion Recognition in AI Audio Models The benchmark targets the expressed emotion — what the speaker conveys through vocal tone, prosody, pace, intensity, and pauses — not inferred internal state. Contents 280 human-recorded English WAV clips, totalling 2.32 hours. 7… See the full description on the dataset page: https://huggingface.co/datasets/besimple-ai/vocal-affect-bench.
Add Gemini 3.8 Flash benchmark through Google
Add Resonance 2 benchmark through Oruk
Add ICASSP 2027 submission manuscript
Prohibit benchmark audio voice cloning
Add Inkling benchmark through Modal
Init Commit
