This paper proposes a statistical intonation model designed to deal with intrinsic variability in speech. In combining the advantages of two well-known statistical algorithms, CART and HMM, the proposed model takes advantage of available linguistic information and successfully tackles the issue of missing para-linguistic information. Promising results of the training process are shown and analyzed. 1. Introduction