Brent (1999a) compares these two models in terms of word tokens correctly segmented (see Section 3 for exact criteria), reporting approximately 40% precision and 45% recall for transitional probability (TP) and 50% precision and 53% recall for mutual information (MI) on the first 1000 utterances of his corpus (with improvements given larger corpora). Indeed, their performance on word tokens is surpassed only by Brent's main model (MBDP-1), which seems to have about 73% precision and 67% recall for the same range.