The paper describes agents for emotion recognition in speech and their application to a real world problem. The agents can recognized five emotional states with the following accuracy: normal or unemotional state - 55-75%, happiness - 60-70%, anger - 70-80%, sadness - 75-85%, and fear - 35-55%. The total average accuracy is about 70%. The agents can be adapted to a particular environment depending on parameters of speech signal and the number of target emotions. For a practical application an agent has been created that is able to analyze telephone quality speech signal and distinguish between two emotional states ("agitation" which includes anger, happiness and fear, and "calm" which includes normal state and sadness) with the accuracy 77%. The agent was used as a part of a decision support system for prioritizing voice messages and assigning a proper human agent to response the message at call center environment.