In this article a generalized Frank copula was selected to model the dependence between the energy on two frequency bands of the speech signal, coming from eight languages. An algorithm was developed that uses maximum likelihood to choose the best fitting copula’s parameters. Through bootstrap, the algorithm estimates the variability of the parameters for each language and also computes confidence regions by means of Voronoi tesselations. A linguistic conjecture which claims that the languages are organized in three rhythmic classes, was confirmed by the Voronoi regions. Modeling with a uniparametric Frank copula, the different degrees of dependence between the energies were quantified.