Studies on the emotion recognition task indicate that there is confusion in discrimination among higher activation states like `anger' and `happy'. In this study, features related to excitation source of speech are examined for discriminating `anger' and `happy' emotions. The objective is to explore the features which are independent of lexical content, language, channel and speaker. The features like strength of excitation from zero frequency filtering method and spectral band magnitude energies from short-time spectral analysis are used. Experimental results show that these features can discriminate `anger' and `happy' emotion states to a good extent.