Customer Satisfaction Recognition through Emotions

Machine Learning

Customer satisfaction is the one of the mandatory things in the day-to-day life like mall customers, organization customers. Here we proposing the facial emotion-based feedback of the customer is happy or not, for that we need to analyze the customers Facial Emotion is a important factor in Human Computer Interaction. Among non-verbal components, facial features are one of the main information channels. Hence, we are proposing a CNN Model and Haar Cascade Classifier to recognize the facial Emotions, Age and Gender to recognize Customer Satisfaction. The technology used is Convolutional Neural Networks from Machine Learning. The dataset consisting of pixel sets of images of people with different Emotions, is used to train the model. The proposed model is a real time model used to detect the face using live video stream and determine the Emotion, and hence in turn determine if the customer is satisfied or not. The main advantage of the proposed system is that it uses real time live video stream through webcam. The key concept of this system is to use Machine Learning algorithm to determine Emotion of Customer.

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