From a theoretical point of view, it can be seen as incorporating discriminative training techniques when working with a generative model by optimizing for segmentation performance rather than maximum a posteriori probability.
only the hyperparameters are optimized in this fashion, whereas the lexicon parameters are still learned within the generative model framework.