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Model-theoretic grammars, also known as constraint-based grammars, contrast with generative grammars in the way they define sets of sentences: they state constraints on syntactic structure rather than providing operations for generating syntactic objects. [1]
A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition [2], machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.
Consequently, a usage-based model accounts for these rule-governed language behaviours by providing a representational scheme that is entirely instance-based, and able to recognize and uniquely represent each familiar pattern, which occurs with varying strengths at different instances. His usage-based model draws on the cognitive psychology of ...
Generative grammar proposes models of language consisting of explicit rule systems, which make testable falsifiable predictions. This is different from traditional grammar where grammatical patterns are often described more loosely. [9] [10] These models are intended to be parsimonious, capturing generalizations in the data with as few rules as ...
The Chomsky hierarchy in the fields of formal language theory, computer science, and linguistics, is a containment hierarchy of classes of formal grammars. A formal grammar describes how to form strings from a language's vocabulary (or alphabet) that are valid according to the language's syntax.
Construction grammar is a family of different theories some of which may be considered functional, such as Croft's Radical Construction Grammar. [41] Relational Network Theory (RNT) or Neurocognitive Linguistics (NCL), originally developed by Sydney Lamb, may be considered functionalist in the sense of being a usage-based model. In RNT, the ...
Chomsky hypothesizes that this device has to be finite instead of infinite. He then considers finite state grammar, a communication theoretic model [note 31] which treats language as a Markov process. [66] Then in the fourth chapter titled "Phrase Structure", he discusses phrase structure grammar, a model based on immediate constituent analysis ...
A stochastic grammar (statistical grammar) is a grammar framework with a probabilistic notion of grammaticality: Stochastic context-free grammar; Statistical parsing; Data-oriented parsing; Hidden Markov model (or stochastic regular grammar [1]) Estimation theory; The grammar is realized as a language model.