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Identity Verification Dataset
Dataset provides 1,215 videos and 405 speech clips of 45 individuals, annotated with gender, ethnicity, and multi-emotion labels. Designed for AI avatar generation, identity verification, and computer vision tasks, this emotional video and speech dataset supports creating realistic avatars, training **deep learning **models, and advancing applications in virtual assistants, facial recognition, and digital identity.
By utilizing this dataset, researchers can develop and benchmark advanced AI models for verifying identity and detecting fraud risks through multi-modal analysis of biometric data from video recordings. - Get the data
Dataset contains recordings of 45 individuals, each performing 3 different sentences. Every sentence is spoken with 3 distinct emotions and captured from 3 different camera angles
Frequently Asked Questions
Why are emotional video recordings useful for KYC applications?
Facial expressions introduce natural variations in appearance that many verification systems encounter during real customer onboarding.
Is the dataset suitable for training AI avatar and digital identity models?
Yes. The accompanying AI avatar data provides consistent facial videos and speech recordings that can support realistic avatar generation, facial animation, identity-preserving synthesis, and digital human research.
Who can benefit from this Video Emotion Recognition Dataset?
This video emotion recognition dataset is valuable for organizations and researchers developing AI systems that analyze facial expressions, emotions, and human behavior from video.
💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.
Researchers and companies can utilize this dataset to significantly improve their recognition technology, enhance security measures, and develop next-generation biometric authentication that effectively prevents spoofing and ensures reliable identity verification.
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