Human Emotion Recognition in Speech using Ant Colony Optimization

Abstract

Emotional speech recognition is an area of great interest for human-computer interaction. The system must be able to recognize  the  user’s emotion and perform the actions accordingly. It is essential to have a framework that includes various modules performing  actions like speech to text conversion, feature extraction, feature selection and classification of those features to identify the emotions.  The classifications of features involve the training of various emotional models to perform the classification appropriately. Another important aspect to be considered in emotional speech recognition is the database used for training the models [1].