An implementation of anger detection in speech signals

In this paper, an emotion classification system based on speech signals is presented. The classifier can identify the most common emotions, namely anger, neutral, happiness and fear. The algorithm computes a number of acoustic features which are fed into the classifier based on a pattern recognition approach. The classification system is of potential benefit for ambient intelligence in which the emotional and physical states of a person should be known to the intelligence of the environment. Using such information, the environment can better support humans in their daily activities in accordance with their preferences.