Tree-adjoining grammar

About: Tree-adjoining grammar is a research topic. Over the lifetime, 2491 publications have been published within this topic receiving 57813 citations.

A grammar-based approach towards unifying hierarchical data models

Abstract: A simple model for representing the hierarchical structure of information is proposed. This model, called the grammatical model, is based on trees that are generated by grammars; the grammars describe the hierarchy of the information represented by the trees. Two transformation languages, an algebra and a calculus, are presented and shown to be equally expressive.

Grammars with partial ordering of the rules

Abstract: It is proved that the languages generated by context-free grammars, whose rules are partially ordered, constitute an intermediate class between the context-free and context-sensitive languages; the first inclusion is shown to be proper.

D-tree substitution grammars

Abstract: There is considerable interest among computational linguists in lexicalized grammatical frame-works; lexicalized tree adjoining grammar (LTAG) is one widely studied example. In this paper, we investigate how derivations in LTAG can be viewed not as manipulations of trees but as manipulations of tree descriptions. Changing the way the lexicalized formalism is viewed raises questions as to the desirability of certain aspects of the formalism. We present a new formalism, d-tree substitution grammar (DSG). Derivations in DSG involve the composition of d-trees, special kinds of tree descriptions. Trees are read off from derived d-trees. We show how the DSG formalism, which is designed to inherit many of the characterestics of LTAG, can be used to express a variety of linguistic analyses not available in LTAG.

Method and apparatus for creating speech recognition grammars constrained by counter examples

Abstract: An automated system generates and revises grammars for speech recognizers in a speech recognition system. Given an initial grammar, expressed in terms of non-terminals in Backus-Naur Form (BNF) notation, a sentence generator generates a list of all sentences accepted by the grammar. From this list, a corpus of inappropriate or irrelevant sentences which are accepted by the grammar (counter-examples) is identified. A grammar revisor program uses the original grammar and the list of counter examples, to generate a pruned list from which a revised grammar is generated. The revision process is iterated several times either concatenating or merging pairs of non-terminals until the revised grammar is deemed satisfactory in that it accepts as legal only relevant sentences. The revised grammar is used by the speech recognizer, thus reducing errors in the overall system.

Evolving stochastic context-free grammars from examples using a minimum description length principle

Abstract: This paper describes an evolutionary approach to the problem of inferring stochastic context-free grammars from finite language samples. The approach employs a genetic algorithm, with a fitness function derived from a minimum description length principle. Solutions to the inference problem are evolved by optimizing the parameters of a covering grammar for a given language sample. We provide details of our fitness function for grammars and present the results of a number of experiments in learning grammars for a range of formal languages. Keywords: grammatical inference, genetic algorithms, language modelling, formal languages, induction, minimum description length. Introduction Grammatical inference (Gold 1978) is a fundamental problem in many areas of artificial intelligence and cognitive science, including speech and language processing, syntactic pattern recognition and automated programming. Although a wide variety of techniques for automated grammatical inference have been devis..