Speech interaction allows humans to convey complex beliefs and desires efficiently. Thus, speech interfaces are a natural candidate for making robots useful to the general public in a flexible and autonomous way. However, language use is an inherently discrete, symbolic task, while robots exist in a continuous world of noisy sensorimotor data. The problem of language grounding, connecting words to the real world, has been addressed by a number of researchers (see [27,28], and Section 4 below). Most implemented approaches extract discrete models and labels from sensor **data** as a foundation for symbolic language use.