Shivam Kumar
Rameshber Goswami
Yash Tripathi
Srishti Malu
Anjuli Dubey
- Student Department of Computer Engineering, Poornima College of Engineering, Jaipur Rajasthan India
- Student Department of Computer Engineering, Poornima College of Engineering, Jaipur Rajasthan India
- Student Department of Computer Engineering, Poornima College of Engineering, Jaipur Rajasthan India
- Student Department of Computer Engineering, Poornima College of Engineering, Jaipur Rajasthan India
- Assistant Professor Department of Computer Engineering, Poornima College of Engineering, Jaipur Rajasthan India
Abstract
In this paper, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends a song or music that matches a user’s mood. The deep learning model used in the given system is trained on the FER-2013 dataset, which is nothing more than an annotated dataset of facial images. The system is based on real-time video feeds, which recommend an emotional level based on a user’s emotional state. Thus, the presented system is a widely innovative tool that has the potential to revolutionize music consumption and generally improve the user’s state through accurate mood-based music selection. A performance assessment involving a labeled image dataset resulted in a detection accuracy rate of around 81%. Subsequent user studies ensured the system’s ability to recommend music tunes, which accurately reflect the user’s mood and personality.
Keywords: Deep learning, computer vision, Deep CNN, Facial Recognition Technology, Emotion Recognition, Music Recommendation System, Vision, Machine Learning, Convolutional Neural Network, Mood Detection.
[This article belongs to Journal of Artificial Intelligence Research & Advances(joaira)]
References
Journal of Artificial Intelligence Research & Advances
Volume | 11 |
Issue | 02 |
Received | May 6, 2024 |
Accepted | June 30, 2024 |
Published | July 10, 2024 |
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