Facial Emotion Recognition from Speech, Text and Facial using Python
In automobiles, safety is important factor and driver factor is most efficient for road safety and it found that 90% of road accident are due to driver fault. The driver emotion plays a important role in ensuring safety while driving. Thus detecting driver emotion could improve road accident. This model involves detecting or identifying driver emotions. Artificial Intelligence technologies helped automate and improve many aspects of driving, AI Technologies to detect emotions of driver as Happy, Sad, Angry, Fear, Disgust by considering both speech and facial emotions, which include audio and visual alert for safety and it improves the driver emotion state by suggestion provided by a music recommendation system. This project use of deep learning models (CNN Models) for automatic emotion detection from audio and video where validation accuracy obtained for audio emotion detection and video emotion detection is 78% and 83%. This project uses the Spotify API for music recommendation system.
Facial Emotion Recognition using CNN
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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