International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 08 | Aug 2023
p-ISSN: 2395-0072
www.irjet.net
Human Emotion Detection for Customer Feedback & Food Classifier Ayesha Samreen 1, Srividya M.S 2 1PG student, Department of Computer Science & Engineering, RV College of Engineering, Bengaluru-560059, India 2Assistant Professor, Department of Computer Science & Engineering, RV College of Engineering, Bengaluru-
560059, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This study analyses the level to which hotel
as “please rate the ambience of the hotel with respect to your experience” or “please indicate through a gesture how you felt about the food”. When the response is recorded, based on the intensity of the feeling in the user, the algorithm may classify the response into “excellent “, “outstanding” “happy”, “not satisfactory “etc.
employees are aware of their facial expression/emotion recognition abilities in interacting with customers. As a sign of satisfaction and service quality delivered, facial expressions and emotions may have significant implications. The results show that a significant proportion of hotel employees are not fully aware of their facial expression/emotion recognition abilities and that many of them tend to engorge their abilities. This study has important implications in terms of employee efforts put into tasks (such as effort and concentration), selfdevelopment and training, and employee risk-taking behavior in their service encounters. In addition, Food Recommendation based on Emotion Analysis is proposed. An IoT device which first detects the human emotion and then using its artificial intelligence and pretrained images, suggests some food items to the customers at that moment. For the functioning purpose, we used a pretrained emotion detection model and tested it on an image pretrained images from Kaggle.
This system thus delivers the customer feedback to the service-provider organization, which can then use the information to take corrective measures to improve the quality of service to the end customer. Between food and mood apparently there exists a relationship, various things like eating foods and thinking or reacting etc. Foods and emotions are two different entities which differs from person to person still interconnected. Emotions play an important role in food choice. Studies shows that foods precisely raise the brain neurotransmitter system that have the greater effects on mood. Thus, food can impact our mood and mood can impact our food. Food and emotion are routine and logical components of our lives that is alluring they don’t get confine together. Even though, there are many research on of effect and cause of food and mood relation such as, brain chemicals, neurotransmitters like serotonin, dopamine and acetylcholine can be influenced by eaten and also variations in blood sugar levels are influenced by what we eat. Healthy foods, such as vegetables, fruits, fish, nuts, seeds, help to promote being cheerful, satisfaction and happiness. Few other foods can increase negative feelings, such as frustration, anger, tension, anxiety. Sad: Chocolate, tea, coffee, nuts peanuts, cashew, almonds and walnuts. Angry Tea, coffee, light food like chips, waffles Fear Eggs, nuts, turmeric Disgust Water. For Surprise: water, any available chilled drink. Shown in table1.
Key Words: emotion recognition, facial expressions, etc.
1. INTRODUCTION Feedback is a vital part in the process of self- improvement in any service sector. This study computes hotel and restaurant service sector. In the conventional model, feedback is collected by means of questionnaires (whether manual or digital), and through online screens or kiosks. The model displays various delicacy messages related to the customers overall experience of the service. This proposed application can be technologically advanced by incorporating digital video cameras to capture the mood/emotion of the customers at various key strategic places within the vicinity of the particular hotel or restaurant outlet and by using artificial intelligence and machine learning to extract frames from the continuous video stream to record the exact emotion expressed by the customer with respect to and in reaction to the various services offered by the soliciting organization.
2. LITERATURE SURVEY
These frames which includes emotions displayed by the consumer is passed through various established human emotion detection algorithms to extract the exact feeling felt by customer in response to the service efficiency of the service provided.
[1] This system proposes sentiment analysis model based on images. Pretrained models (VGG-19, DenseNet121, and ResNet50V2) are compared to predict the sentiments from pictures. The performance of the model is improved by freezing the initial layers and unfreezing part of the model. Over fitting effect is been reduced by addition of layers like dropout, batch normalization, and weight regularization layers in turn helped to predict sentiments from the database. With DenseNet121 model 0.89 accuracy is obtained for image sentiment analysis.
For instance, when a user passes in front of such a cameracum-display device, the device may display a message such
[2] This research work uses social media platforms, which is the easiest way to express emotions pertaining to any
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