Speech Emotion Recognition using Dialogue Emotion Decoder and CNN Classifier

Recently, everywhere in the world for the purpose of recognizing the emotions research are carried out. Understanding a person's true state at the time they are uttering words is the first stage of determining their emotions from their speech. One's voice pitch also determines the state of the emotion. Eventually, in this paper the emotions are extracted in five forms (Excite, anger, happiness, neutrality, and sadness). After the pre-processing of the input speech data the dataset is ready for the feature extraction using Dialogue Emotion Decoder (DED) and CNN classifier to give the output of the utterances in the form of emotions.