This paper describes the AuToBI system for automatic generation of hypothesized ToBI labels. While research on automatic prosodic annotation has been conducted for many years, AuToBI represents the first publicly available tool to automatically detect and classify the prosodic events that make up the ToBI annotation standard. This paper describes the feature extraction routines as well as the classifiers used to detect and classify ToBI tones. Additionally, we report performance evaluating AuToBI models trained on the Boston Directions Corpus on the Columbia Games Corpus. By reporting performance on distinct speakers, domains and recording conditions, this evaluation describes an accurate expectation of the performance of the system when applied to other material.