Abstract

Our lives are being significantly impacted by the rapid development of wire- less technology and mobile gadgets on this day. The digital economy demands that services be developed almost instantly while also paying close attention to client feedback. It becomes difficult to manage and analyse the informa- tion gathered about products from customers. Successful businesses typically gather reasonable input on customer behaviour, comprehend their clients, and maintain ongoing contact with them. But it’s not an easy task to keep a record of each and every customer’ feedback on a daily basis. Also, everyone is not intended to provide clear feedback whether the product was satisfactory or not. It is a very difficult and time-consuming task to analyse the data collected man- ually. Companies need automation of customer feedback processing in order to quickly use the data that has been collected and analyse consumer feedback. To proceed with the problem and through much research we came across a solution, Emotica.AI, an emotion recognition system which can overcome this situation in real time. Emotion recognition plays an important role in building interpersonal relationships. Speaking, making facial expressions, gesturing, or writing are all ways that people directly or indirectly convey their feelings. Now that AI has mastered the power of learning, it is capable of treating any- thing just like a human would. The proposed model is built with Haar-Cascade Algorithm and classified with CNN and is able to recognise the emotions of multiple faces in a real time scenario. Accuracy of this model is around 76% is achieved for seven emotions on a real -time basis. Our goal is to develop a real time implementation of an emotion detection system with better accuracy and make it more reliable for businesses and other purposes.