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Unsupervised Learning of Syntactic Structure
This video was recorded at Workshop on Machine Learning and Cognitive Science of Language Acquisition, London 2007. Probabilistic models of language. ''Everybody knows that language is variable'' - Sapir (1921). Probabilistic models give precise descriptions of a variable, uncertain world. The choice for language isn't a dichotomy between rules and neural networks. Probabilistic models can be used over rich linguistic representations. They support inference and learning. There's not much evidence of a poverty of the stimulus preventing them being used.
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