affect
Datasets
All datasets matching “affect”AffectNet-Mediapipe-478Points-3Dambivalent_affectgspc-affect
GSPC — affect bank (AffectBench)
Council of AI measurement bank. Measurement, not certification.
Bank. Frozen split. Live n is the matching axis on GET https://councilof.ai/api/gspc, not a Hub score. Not a certificate. Art 50 (EUR-Lex): 2 August 2026 live; marking grace 2 December 2026.
Live measurement. This bank stands behind the affect row of the live GSPC board: GET https://councilof.ai/api/gspc?axis=affect (family, kind, status and n are on that row, never typed here; the… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-affect.n4x7d2q9-hf1m8t3_tran
affectexpect/n4x7d2q9-hf1m8t3_tran
This dataset contains transcribed audio files organized in folders for scalability.
Dataset Structure
The dataset is organized with:
Audio files: Stored in audio_XXXXX/ folders (5000 files per folder)
Metadata: Stored in data_XXXXX/ folders as parquet files
This organization follows Hugging Face best practices for datasets with millions of files.
Statistics
Total files: 922
Total batches: 11336
Audio folders: 10… See the full description on the dataset page: https://huggingface.co/datasets/affectexpect/n4x7d2q9-hf1m8t3_tran.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.affectnet_short
Dataset Card for "affectnet_short"
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