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.