The majority of machine learning research assumes that the data used for building a model and making inference are sampled from the same distribution, i.e., the data generation process is stationary.
because of its online characteristic, one challenge faced by FSD models is that the system's vocabulary (and hence document representation) cannot be derived from a target corpus, but must instead be defined by the vocabulary of a background corpus.