3 papers
cs.SD2026
VoiceNet: Fine-Grained Voice Understanding Beyond Emotion at Scale
Christoph Schuhmann, Robert Kaczmarczyk, Gollam Rabby +7
Expressive speech synthesis has outpaced expressive speech perception: systems now render fine-grained vocal performances that no public benchmark can score. Most benchmarks for th…
cs.CL2025
EmoNet-Voice: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detection
Christoph Schuhmann, Robert Kaczmarczyk, Gollam Rabby +6
Speech emotion recognition (SER) systems are constrained by existing datasets that typically cover only 6-10 basic emotions, lack scale and diversity, and face ethical challenges w…
cs.CV2025
EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition
Christoph Schuhmann, Robert Kaczmarczyk, Gollam Rabby +7
Effective human-AI interaction relies on AI's ability to accurately perceive and interpret human emotions. Current benchmarks for vision and vision-language models are severely lim…