A new syntactic model, called pure 2D context-free grammar (P2DCFG), is introduced based on the notion of pure context-free string grammar. The rectangular picture generative power of this 2D grammar model is investigated. Certain closure properties are obtained. An analogue of this 2D grammar model called pure 2D hexagonal context-free grammar (P2DHCFG) is also considered to generate hexagonal...

Several grammars have been proposed for representing RNA secondary structure including pseudoknots. In this paper, we introduce subclasses of multiple context-free grammars which are weakly equivalent to these grammars for RNA, and clarify the generative power of these grammars as well as closure property.

Many formal models have been proposed to recognize or to generate two-dimensional words. In this paper, we focus our analysis on (regular) pure 2D context-free grammars, regional tile grammars and Pr̊uša grammars, showing that nevertheless they have been proposed as a generalization of string context free grammars their expressiveness is different. This work refines the relationship among the cl...

Over the last decade, probabilistic parsing has become the standard in the parsing literature where one of the purposes of those probabilities is to discard unlikely parses. We investigate the effect that discarding low probability parses has on both the weak and strong generative power of context-free grammars. We prove that probabilistic context-free grammars are more powerful than their non-...

We propose a new graphical model, called Sequential Interval Network (SIN), for parsing complex structured activity whose composition can be represented as a string-length limited stochastic context-free grammar. By exploiting the grammar, the generated network captures the activity’s global temporal structure while avoiding time-sliced manner model. In this network, the hidden variables are th...

Integration of two stochastic context-free grammars can be useful in two pass approaches used, for example, in speech recognition and understanding. Based on an algorithm proposed by [Nederhof and Satta, 2002] for the non-probabilistic case, left-to-right strategies for the search for the best solution based on CKY and Earley parsers are discussed. The restriction that one of the two grammars m...

We show how to encode context-free string grammars, linear contextfree tree grammars, and linear context-free rewriting systems as Abstract Categorial Grammars. These three encodings share the same constructs, the only difference being the interpretation of the composition of the production rules. It is interpreted as a first-order operation in the case of context-free string grammars, as a sec...

In this paper, we propose a new framework for online handwritten mathematical expression recognition. In this approach, we consider handwritten mathematical expressions as the output of stroke generation processes based on a stochastic context-free grammar which generates handwritten expressions stochastically. We estimate the most likely expression candidate derived from the grammar, rather th...

We propose a class trigram language model in which each class is specified by a stochastic context-free grammar. We show how to estimate the parameters of the model, and how to smooth these estimates. We present experimental perplexity and speech recognition results.

We discuss some of the practical issues that arise from decoding with general synchronous context-free grammars. We examine problems caused by unary rules and we also examine how virtual nonterminals resulting from binarization can best be handled. We also investigate adding more flexibility to synchronous context-free grammars by adding glue rules and phrases.