An Incremental Bayesian Model for Learning Syntactic Categories

  title={An Incremental Bayesian Model for Learning Syntactic Categories},
  author={Christopher Parisien and Afsaneh Fazly and Suzanne Stevenson},
We present an incremental Bayesian model for the unsupervised learning of syntactic categories from raw text. The model draws information from the distributional cues of words within an utterance, while explicitly bootstrapping its development on its own partiallylearned knowledge of syntactic categories. Testing our model on actual child-directed data, we demonstrate that it is robust to noise, learns reasonable categories, manages lexical ambiguity, and in general shows learning behaviours… CONTINUE READING


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