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ACL
2008
13 years 6 months ago
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
Mark Johnson
COLING
2010
12 years 11 months ago
Unsupervised phonemic Chinese word segmentation using Adaptor Grammars
Adaptor grammars are a framework for expressing and performing inference over a variety of non-parametric linguistic models. These models currently provide state-of-the-art perfor...
Mark Johnson, Katherine Demuth
ACL
2012
11 years 7 months ago
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
This paper uses an unsupervised model of grounded language acquisition to study the role that social cues play in language acquisition. The input to the model consists of (orthogr...
Mark Johnson, Katherine Demuth, Michael C. Frank