A typical application for unsupervised morphological segmentation involves situations in which we are confronted with a low-resource language for which no prior NLP work exists, and for which we cannot annotate even a small corpus (either for lack of time, or because no annotators are available).
in this paper, we are interested in remaining language-independent and entirely unsupervised.