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The fact that in Thai language emotions are not usually manifested, mostly because any emotion would interfere with meaning otherwise, makes this language very difficult for any kind of emotion recognition. Our proposed Thai emotion recognition system consists of two parts - speech emotion recognition and improvements of the system using face feature analysis. For this purpose audiovisual Thai emotion database was recorded. Speech emotion recognition is based on calculating fundamental frequency, zero crossing rate and energy from short-time wavelet signals, and shows great system results with accuracy of 97.8%. Our current research activities are directed to improving the accuracy of the overall system using face feature analysis, therefore showing that vision is as crucial as hearing is for expressing and recognizing any emotion.