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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The authors present a novel non-parametric Bayesian model for unsupervised clustering. The model uses a two level hierarchy of Dirichlet process priors to handle clusters which may be multi-modal, skewed and/or heavy tailed. The authors present a collapsed Gibbs sampler for inference which exploits the conjugacy of the model. The authors do an excellent job of motivating the model by explaining the deficiencies of the standard infinite mixture of Gaussians.