A diverse dirichlet process ensemble for unsupervised induction of syntactic categories

We address the problem of unsupervised tagging of phrase structure trees with phrase categories (parse tree nonterminals). Motivated by the inability of a range of direct clustering approaches to improve over the current leading algorithm, we propose a mixture of experts approach. In particular, we tackle the difficult challenge of producing a diverse collection of useful tagging experts, which can then be aggregated into a final high-quality tagging. To do so, we use the particular properties of the Dirichlet Process mixture model. We evaluate on English, German and Chinese corpora and demonstrate both a substantial and consistent improvement in overall performance over previous work, as well as empirical justification of our algorithmic choices.