  Veracity is an essential key in research and development of innovative
products. Live Emotion analysis and verification nullify deceit made to
complainers on live chat, corroborate messages of both ends in messaging apps
and promote an honest conversation between users. The main concept behind this
emotion artificial intelligent verifier is to license or decline message
accountability by comparing variegated emotions of chat app users recognized
through facial expressions and text prediction. In this paper, a proposed
emotion intelligent live detector acts as an honest arbiter who distributes
facial emotions into labels namely, Happiness, Sadness, Surprise, and Hate.
Further, it separately predicts a label of messages through text
classification. Finally, it compares both labels and declares the message as a
fraud or a bonafide. For emotion detection, we deployed Convolutional Neural
Network (CNN) using a miniXception model and for text prediction, we selected
Support Vector Machine (SVM) natural language processing probability classifier
due to receiving the best accuracy on training dataset after applying Support
Vector Machine (SVM), Random Forest Classifier, Naive Bayes Classifier, and
Logistic regression.
