International Journal For Multidisciplinary Research

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Emotion AI:Human Psychology Detection

Author(s) Dr. Deepali Makarand Bongulwar, Mr. Prathamesh Suryawanshi, Ms. Rajashri Barik, Mr. Prathamesh Shirsat, Ms. Pratiksha Kude
Country India
Abstract This research explores the use of the state-of-the-art transformer-based pre-trained model, the ViT-Face-Expression model from Hugging Face, for human psychology detection from audio and video data. Our technique seeks to provide a full knowledge of human emotions and underlying psychological states by fusing aural cues with visual information gathered from facial expressions. Specifically designed to capture facial emotions within Vision Transformers (ViT), the ViT- Face-Expression model provides a potent tool for deciphering complex emotional nuances stored in facial features. By combining this model with audio processing methods, human psychology can be understood holistically, leading to more accurate identification of emotions and progress in the field of emotion artificial intelligence.
Through the integration of visual and aural modalities in emotion recognition, this research advances the rapidly developing subject of Emotion AI. Through the application of audio processing methods in conjunction with the capabilities of the ViT-Face-Expression model, Samlowe model for audio and our goal is to improve the precision and resilience of emotion identification systems. In order to better understand human emotions, our research highlights the significance of taking into account both auditory and visual clues. This will help to develop AI systems that are more sympathetic and context-aware.
Keywords Vit Face Expression, Hugging Face, Samlowe, OpenAI, OpenCV
Field Engineering
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-07-15
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.50599
Short DOI https://doi.org/g9s9mh
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