Grammatical Inference and Applications

This volume presents the proceedings of the Second International Colloquium on Grammatical Inference (ICGI-94), held in Alicante, Spain in September 1994.
Besides 25 research papers carefully selected and refereed by the program committee, the book contains a survey by E. Vidal. The book is devoted to all those aspects of automatic learning that explicitly focus on principles, theory, and applications of grammars and languages. The papers are organized in sections on formal aspects; language modelling and linguistic applications; stochastic approaches, applications and performance analysis; and neural networks, genetic algorithms, and artificial intelligence techniques.

Inhalt
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 EnglishCorpus.- Stochastic optimization of a probabilistic language model.- Computer assisted grammar construction.