Two applications of statistically-generated decision trees to problems in speech synthesis are described: (1) End of sentence detection: A decision tree is generated to decide when a period in text corresponds to the end of a declarative sentence (and not an abbreviation). The result is 99.8% correct classification on the Brown corpus. (2) Segment duration modelling in speech synthesis: 1500 utterances from a single speaker were used to a build a decision tree that predicts segment durations based on features such as lexical position, stress, and phonetic context. The result is prediction with residuals with a 23 millisecond standard deviation and synthesis that compares favorably with current hand-generated duration rules.