Perceptual experiments with infants show that they adapt their perception of speech sounds toward the categories of the native language. How do infants learn these categories? For the most part, acoustic analyses of natural infant-directed speech have suggested that phonetic categories are not presented to learners as separable clusters of sounds in acoustic space. As a step toward explaining how infants begin to solve this problem, the current study proposes that the exaggerated prosody characteristic of infant-directed speech may highlight for infants certain speech-sound tokens that collectively form more readily identifiable categories. A database is presented, containing vowel measurements in a large sample of natural American English infant-directed speech. Analyses of the vowel space show that prosodic exaggeration in infant-directed speech has the potential to support distributional vowel learning by providing the learner with a subset of "high-quality" tokens that infants might attend to preferentially. Categorization models trained on prosodically exaggerated tokens outperformed models that were trained on tokens that were not exaggerated. Though focusing on more prominent, exaggerated tokens does not provide a solution to the categorization problem, it would make it easier to solve.