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This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences.

The topics chosen are of foundational interest with relatively mature and established...

Stress and accent are central, organizing features of grammar, but their precise nature continues to be a source of mystery and wonder. These issues come to the forefront in acquisition, where the tension between the abstract mental representations and the concrete physical manifestations of stress and accent is deeply reflected. Understanding the nature of the representations of stress and accent patterns, and understanding how stress and accent patterns are learned, informs all aspects of linguistic theory and language acquisition. These two themes - representation and acquisition - form...

This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols. The relationship to computational linguistics is natural because many research problems in computational linguistics are learning problems on words, phrases, and sentences: What algorithm can take as input some finite amount of data (for instance a corpus, annotated or otherwise) and...