It can be shown that the model selection in our method is equivalent to a MAP inference, conducted under the assumption that the prior probability of a model decreases exponentially with its length (Goldwater, 2006).
similarly, when the corpus is broken down into single-character tokens, merging individual pairs does not produce any increase in compression.