Context-sensitive grammar

About: Context-sensitive grammar is a research topic. Over the lifetime, 1938 publications have been published within this topic receiving 45911 citations. The topic is also known as: CSG.

Automatic generation of efficient evaluators for attribute grammars

Abstract: The translation process may be divided into a syntactic phase and a semantic phase. Context-free grammars can be used to describe the set of syntactically correct source texts in a formal yet intuitively appealing way, and many techniques are now known for automatically constructing parsers from given CF grammars. Knuth's attribute grammars offer the prospect of similarly automating the implementation of the semantic phase. An attribute grammar is an ordinary CF grammar extended to specify the “meaning” of each string in the language. Each grammar symbol has an associated set of “attributes:”, and each production rule is provided with corresponding semantic rules expressing the relationships between the attributes of symbols in the production. To find the meaning of a string, first we find its parse tree and then we determine the values of all the attributes of symbols in the tree.

Systems and methods for generating weighted finite-state automata representing grammars

Abstract: A context-free grammar can be represented by a weighted finite-state transducer. This representation can be used to efficiently compile that grammar into a weighted finite-state automaton that accepts the strings allowed by the grammar with the corresponding weights. The rules of a context-free grammar are input. A finite-state automaton is generated from the input rules. Strongly connected components of the finite-state automaton are identified. An automaton is generated for each strongly connected component. A topology that defines a number of states, and that uses active ones of the non-terminal symbols of the context-free grammar as the labels between those states, is defined. The topology is expanded by replacing a transition, and its beginning and end states, with the automaton that includes, as a state, the symbol used as the label on that transition. The topology can be fully expanded or dynamically expanded as required to recognize a particular input string.

Regular Approximation of Context-Free Grammars through Transformation

Abstract: We present an algorithm for approximating context-free languages with regular languages. The algorithm is based on a simple transformation that applies to any context-free grammar and guarantees that the result can be compiled into a finite automaton. The resulting grammar contains at most one new nonterminal for any nonterminal symbol of the input grammar. The result thus remains readable and if necessary modifiable. We extend the approximation algorithm to the case of weighted context-free grammars. We also report experiments with several grammars showing that the size of the minimal deterministic automata accepting the resulting approximations is of practical use for applications such as speech recognition.