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This paper describes the use of statistical techniques and Hidden Markov Models (HMM) in the recognition of emotions. The method aims to classify 6 basic emotions (angry, dislike, fear, happy, sad and surprise) from both facial expressions (video) and emotional speech (audio). The emotions of 2 human subjects were recorded and analyzed. The findings show that the audio and video information can be combined using a rule-based system to improve the recognition rate.