We describe experiments designed to learn associations between two types of intonational features, pitch accent and phrasing, from a tree-based corpus annotated with various intonational and syntactic features, for a concept-to-speech system. We show that using novel tree-based features improves the quality of boundary prediction over using only the linear order-based features normally used in text-to-speech.