In this work, the capability of voice quality parameters to discriminate among different expressive speech styles is analyzed. To that effect, the data distribution of these parameters, directly measured from the acoustic speech signal, is used to train a Linear Discriminant Analysis that conducts an automatic classification. As a result, the most relevant voice quality patterns for discriminating expressive speech styles are obtained for a diphone and triphone Spanish speech corpus with five expressive speaking styles: neutral, happy, sad, sensual and aggressive.