This paper introduces Stem-ML, which is a model of the prosody generation process with an associated description language, and suggests how it may help prosody recognition. We applied Stem-ML modeling to three topics: the modeling of prosodic strengths, intonation types, and noun phrase patterns. Stem-ML parameters derived from F0 contours may have a more consistent relationship with prosodic events than raw F0 values. This may improve identification of accent classes, accent strengths, and intonation types.