long story and narrated it subsequently. All this material was obtained in four language varieties: Brazilian and European Portuguese, standard French and German. The corpus is balanced for gender. Eight melodic and intensity parameters were automatically obtained from excerpts of 10 to 20 seconds. We showed that 6 out of 8 parameters partially distinguish professional from non-professional style in the four language varieties. Classification and discrimination tests carried out with 12 Brazilian listeners using delexicalised speech showed that these subjects are able to distinguish professional style from non-professional style with about 2/3 of hits irrespective of language. In comparison, an automatic classification using an LDA model performed better in classifying non-professional (96 %) against professional styles, but not in classifying professional (42 %) against non-professional styles.