  We present a stochastic finite-state model for segmenting Chinese text into
dictionary entries and productively derived words, and providing pronunciations
for these words; the method incorporates a class-based model in its treatment
of personal names. We also evaluate the system's performance, taking into
account the fact that people often do not agree on a single segmentation.
