13079001
Dynamic programming for parsing and estimation of stochastic unification-based grammars
Stochastic unification-based grammars (SUBGs) define exponential distributions over the parses generated by a unification-based grammar (UBG). Existing algorithms for parsing and estimation require the enumeration of all of the parses of a string in order to determine the most likely one, or in order to calculate the statistics needed to estimate a grammar from a training corpus. This paper describes a graph-based dynamic programming algorithm for calculating these statistics from the packed UBG parse representations of Maxwell and Kaplan (1995) which does not require enumerating all parses. Like many graphical algorithms, the dynamic programming algorithm's complexity is worst-case exponential, but is often polynomial. The key observation is that by using Maxwell and Kaplan packed representations, the required statistics can be rewritten as either the max or the sum of a product of functions. This is exactly the kind of problem which can be solved by dynamic programming over graphical models.
3264258
Type-driven semantic interpretation and feature dependencies in R-LFG
Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constraints fall out as a by-product of the linear logic machinery they propose for semantic interpretation, thus making those f-structure mechanisms redundant. Given that linear logic machinery or something like it is independently needed for semantic interpretation, it seems reasonable to explore the extent to which it is capable of handling feature structure constraints as well. 
R-LFG represents the extreme position that all linguistically required feature structure dependencies can be captured by the resource-accounting machinery of a linear or similiar logic independently needed for semantic interpretation, making LFG's unification machinery redundant. The goal is to show that LFG linguistic analyses can be expressed as clearly and perspicuously using the smaller set of mechanisms of R-LFG as they can using the much larger set of unification-based mechanisms in LFG: if this is the case then we will have shown that positing these extra f-structure mechanisms is not linguistically warranted.
2234445
Attention Shifting for Parsing Speech
We present a technique that improves the efficiency of word-lattice parsing as used in speech recognition language modeling. Our technique applies a probabilistic parser iteratively where on each iteration it focuses on a different subset of the word-lattice. The parser's attention is shifted towards word-lattice subsets for which there are few or no syntactic analyses posited. This attention-shifting technique provides a six-times increase in speed (measured as the number of parser analyses evaluated) while performing equivalently when used as the first-stage of a multi-stage parsing-based language model.
9027893
A Look at Parsing and Its Applications
This paper provides a brief introduction to recent work in statistical parsing and its applications. We highlight successes to date, remaining challenges, and promising future work.
5925726
A Resource Sensitive Interpretation of Lexical Functional Grammar
This paper investigates whether the fundamental linguistic insights and intuitions of Lexical Functional Grammar (LFG), which is usually presented as a “constraint-based” linguistic theory, can be reformulated in a “resource sensitive” framework using a substructural modal logic. In the approach investigated here, LFG's f-descriptions are replaced with expressions from a multi-modal propositional logic (with permutation and possibly limited contraction). In effect, the feature structure “unification” basis of LFG's f-structures is replaced with a very different resource based mechanism. It turns out that some linguistic analyses that required non-monotonic devices in LFG (such as the “constraint equations” in the Andrews (1982) analysis of Icelandic) can be straightforwardly expressed in the framework presented here. Moreover, a Curry–Howard correspondence between proofs in this logic and λ-terms provides a semantic interpretation as a by-product of the process of showing syntactic well-formedness.
2965282
Exploiting auxiliary distributions in stochastic unification-based grammars
This paper describes a method for estimating conditional probability distributions over the parses of "unification-based" grammars which can utilize auxiliary distributions that are estimated by other means. We show how this can be used to incorporate information about lexical selectional preferences gathered from other sources into Stochastic "Unification-based" Grammars (SUBGs). While we apply this estimator to a Stochastic Lexical-Functional Grammar, the method is general, and should be applicable to stochastic versions of HPSGs, categorial grammars and transformational grammars.
1340064
Sub-banded reconstructed phase spaces for speech recognition
A novel method combining filter banks and reconstructed phase spaces is proposed for the modeling and classification of speech. Reconstructed phase spaces, which are based on dynamical systems theory, have advantages over spectral-based analysis methods in that they can capture nonlinear or higher-order statistics. Recent work has shown that the natural measure of a reconstructed phase space can be used for modeling and classification of phonemes. In this work, sub-banding of speech, which has been examined for recognition of noise-corrupted speech, is studied in combination with phase space reconstruction. This sub-banding, which is motivated by empirical psychoacoustical studies, is shown to dramatically improve the phoneme classification accuracy of reconstructed phase space-based approaches. Experiments that examine the performance of fused sub-banded reconstructed phase spaces for phoneme classification are presented. Comparisons against a cepstral-based classifier show that the proposed approach is competitive with state-of-the-art methods for modeling and classification of phonemes. Combination of cepstral-based features and the sub-band RPS features shows improvement over a cepstral-only baseline.
7031742
The effect of pruning and compression on graphical representations of the output of a speech recognizer
Large vocabulary continuous speech recognition can benefit from an efficient data structure for representing a large number of acoustic hypotheses compactly. Word graphs or lattices have been chosen as such an efficient interface between acoustic recognition engines and subsequent language processing modules. This paper first investigates the effect of pruning during acoustic decoding on the quality of word lattices and shows that by combining different pruning options (at the model level and word level), we can obtain word lattices with comparable accuracy to the original lattices and a manageable size. In order to use the word lattices as the input for a post-processing language module, they should preserve the target hypotheses and their scores while being as small as possible. In this paper, we introduce a word graph compression algorithm that significantly reduces the number of words in the graphical representation without eliminating utterance hypotheses or distorting their acoustic scores. We compare this word graph compression algorithm with several other lattice size-reducing approaches and demonstrate the relative strength of the new word graph compression algorithm for decreasing the number of words in the representation. Experiments are conducted across corpora and vocabulary sizes to determine the consistency of the pruning and compression results.
5650913
Dynamic Plasticity Influences the Emergence of Function in a Simple Cortical Array
In computational experiments with a simplified cortical array we investigated the factors that give rise to the functional organization of the cerebral cortex during brain development. We show that a dynamical spatial modulation of plasticity in the substrate (i.e., a "wave of plasticity") induces higher functional development in the later-developing parts of the cortical array. This result suggests an account of the role that changes in developmental timing may have in the development of different cortical structures. Copyri
39453826
A software debugging glossary
This glossary contains 291 definitions of terms dealing with the debugging of computer software. The list includes numerous synonyms, as well as the proper names of debugging systems described in the open literature. Terms and definitions have been obtained from various sources: the software-engineering literature, other software-engineering glossaries, and individual contributions.
8126535
An adaptive approach for texture modelling
Markov random fields (MRFs) continue to be an important and useful representation for modelling textured images. Standard methods for MRF image modeling make use of the equivalent Gibbs distribution (GD) to express the joint probabilities of groups of neighboring pixels. The authors investigate a new approach to the use of the GD in image modeling. Specifically, they develop an adaptive approach to the formation of clique potential functions for the distribution. Traditional tools, such as the multi-level logistic (MLL) model, have been based on the use of a predetermined and identical set of potential functions. In the present paper it is shown that by incorporating additional parameters into the model in order to control the shape of these functions, it is possible to arrive at a more complete parametrization of the image. A simple model based on this concept is described and implemented, and image simulations using the well-known Gibbs sampler algorithm are constructed to demonstrate the usefulness of an adaptive set of potential functions.<<ETX>>