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.

中文翻译：

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谎言传感器：使用情感智能的实时情感验证程序或聊天应用程序的许可人

准确性是研发创新产品的关键。实时情感分析和验证可以消除实时聊天中对投诉者的欺骗，在消息传递应用程序中确认两端的消息，并促进用户之间的诚实对话。这种情绪人工智能验证器背后的主要概念是，通过比较通过面部表情和文本预测识别的聊天应用程序用户的各种情绪，来许可或拒绝消息问责制。在本文中，一种拟议的情绪智能实时检测器充当诚实的仲裁者，将面部情绪分配到“幸福”，“悲伤”，“惊喜”和“仇恨”等标签中。此外，它通过文本分类分别预测消息的标签。最后，它将两个标签进行比较，并将消息声明为欺诈或正当行为。