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Emotion is the most important gear for human textual communication with each other via social media. Nowadays, people use text for reviewing or recommending things, sharing opinions, rating their choices or unlikeness, providing feedback for different services, and so on. Bangladeshi people use Bangla to express their emotions. Current research based on sentiment analysis has got low-performance output by using several approaches on detecting sentiment polarity and emotion from Bangla texts. In this study, we have developed four models with the hybrid of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) with various Word Embeddings including Embedding Layer, Word2Vec, Global Vectors (Glove), and Continuous Bag of Words (CBOW) to detect emotion from Bangla texts (words, sentences). Our models can define the basic three emotions; happiness, anger, and sadness. It …