The paper presents a two level lexical stress assignment model for out of vocabulary Slovenian words used in our text-to-speech system. First, each vowel is determined, whether it is stressed or unstressed, and a type of lexical stress is assigned for every stressed vowel. Then, some corrections are made on the word level, according the number of stressed vowels and the length of the word. We applied a machine-learning technique (decision trees or boosted decision trees). The accuracy achieved by decision trees significantly outperforms all previous results. However, the sizes of the trees indicate that the accentuation in the Slovenian language is a very complex problem and a simple solution in the form of relatively simple rules is not possible.