Grammatical Inference and Applications

Grammatical inference: An introductory survey.- Learning morphology — practice makes good.- A hierarchy of language families learnable by regular language learners.- What is the search space of the regular inference?.- A characterization of even Linear Languages and its application to the learning problem.- Object-Oriented inferences in a logical framework for feature grammars.- Automatic determination of a stochastic bi-gram class language model.- The acquisition of a lexicon from paired phoneme sequences and semantic representations.- Inference and estimation of a long-range trigram model.- Application of OSTIA to machine translation tasks.- Inducing probabilistic grammars by Bayesian model merging.- Statistical estimation of Stochastic Context-Free Grammars using the Inside-Outside algorithm and a transformation on grammars.- Statistical inductive learning of regular formal languages.- Learning stochastic regular grammars by means of a state merging method.- Forming grammars for structured documents: an application of grammatical inference.- A comparison of syntactic and statistical techniques for off-line OCR.- The algorithms RT and k-TTI: A first comparison.- Dynamic grammatical representations in guided propagation networks.- A hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning and hierarchical clustering.- Inference of context-free grammars by enumeration: Structural containment as an ordering bias.- Representational issues for context free grammar induction using genetic algorithms.- Regular grammatical inference from positive and negative samples by genetic search: the GIG method.- Training and application of integrated grammar/bigram language models.- Learning unification-based grammars using the Spoken English Corpus.- Stochastic optimization of a probabilistic language model.- Computer assisted grammar construction.