In this paper, we present a new approach for automatic recognition of emotional expressions from spontaneous Slavic speech. The speech corpus used in experiments is built from speech extracts obtained from real call center recordings involving four Slavic languages: Czech, Polish, Russian and Slovak. Five different emotional states, namely: Anger, happiness, sadness, surprise and neutral are represented in the speech corpus. The proposed approach is based on mapping of discrete emotions into two dimensional space defined by the valence and the activation of emotions. This is carried out by using support vector regression combined with forward feature selection.