Unfortunately, in general, Bayesian techniques are computationally difficult to work with.
hierarchical Pitman-Yor process language models (HPYPLMs) are convenient in this regard since (1) inference can be carried out efficiently in a convenient collapsed representation (the "Chinese restaurant franchise") and (2) the posterior predictive distribution from a single sample provides a high quality language model.