 This task is generally applicable when HMM's are applied to different sorts of problems from those for which the tasks of filtering and smoothing are applicable.An example is part-of-speech tagging, where the hidden states represent the underlying parts of speech corresponding to an observed sequence of words.In this case, what is of interest is the entire sequence of parts of speech, rather than simply the part of speech for a single word, as filtering or smoothing would compute.