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An ability that underlies human syntactic knowledge is determining whichwords can appear in the similar structures (i.e. grouping words by theirsyntactic categories). These groupings enable humans to combine structures inorder to communicate complex meanings. A foundational question is how dochildren acquire this ability underlying syntactic knowledge. In exploring thisprocess, we will review various engineering approaches whose goal is similar tothat of a child's -- without prior syntactic knowledge, correctly identify theparts of speech (POS) of the words in a sample of text. In reviewing theseunsupervised tagging efforts, we will discuss common themes that support theadvances in the models and their relevance for language acquisition. Forexample, we discuss how each model judges success (evaluation metrics), the"additional information" that constrains the POS learning (such as orthographicinformation), and the context used to determine POS (only previous word, wordsbefore and after the target, etc). The identified themes pave the way forfuture investigations into the cognitive processes that underpin theacquisition of syntactic categories and provide a useful layout of currentstate of the art unsupervised POS tagging models.

Review of Unsupervised POS Tagging and Its Implications on Language Acquisition