However, in our case "words" are not known a priori: the next section describes how to accomplish this by constructing a nested HPYLM of words and characters, with the associated inference algorithm.
far we have assumed that the unigram G 1 is already given, but of course it should also be generated as Here, a problem occurs: What should we use for G 0 , namely the prior probabilities over words 2 ?