We showed how adaptor grammars can implement a previously investigated model of unsupervised word segmentation, the unigram word segmentation model .

(2007a) presented an adaptor grammar that defines a unigram model of word segmentation and showed that it performs as well as the unigram DP word segmentation model presented by (Goldwater et al., 2006a).

The adaptor grammar that encodes a unigram word segmentation model shown in Figure 1.

(2007), a unigram word segmentation model tends to undersegment and misanalyse collocations as individual words.

The probabilistic formulation of this model is close to our monolingual segmentation model , but it uses a greedy search specifically designed for the segmentation task.

Our segmentation model is based on the notion that stable recurring string patterns within words are indicative of morphemes.

We note that these single-language morpheme distributions also serve as monolingual segmentation models , and similar models have been successfully applied to the task of word boundary detection (Goldwater et al., 2006).