1384
Features as Resources in R-LFG
This paper introduces a non-unification-based version of LFG called R-LFG (Resource-based Lexical Functional Grammar), which combines elements from both LFG and Linear Logic. The paper argues that a resource sensitive account provides a simpler treatment of many linguistic uses of non-monotonic devices in LFG, such as existential constraints and constraint equations.
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.
739426
Joint and Conditional Estimation of Tagging and Parsing Models
This paper compares two different ways of estimating statistical language models. Many statistical NLP tagging and parsing models are estimated by maximizing the (joint) likelihood of the fully-observed training data. However, since these applications only require the conditional probability distributions, these distributions can in principle be learnt by maximizing the conditional likelihood of the training data. Perhaps somewhat surprisingly, models estimated by maximizing the joint were superior to models estimated by maximizing the conditional, even though some of the latter models intuitively had access to "more information".
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.
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.
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.
678679
Sympathetic interfaces: using a plush toy to direct synthetic characters
We introduce the concept of a sympathetic inter$ace forcontrolling an animated synthetic character in a 3D virtualenvironment. A plush doll embedded with wireless sensors is used tomanipulate the virtual character in an iconic and intentionalmanner. The interface extends from the novel physical input devicethrough interpretation of sensor data to the behavioral brain ofthe virtual character. We discuss the design of the interface andfocus on its latest instantiation in the Swamped! exhibit atSIGGRAPH 98. We also present what we learned from hundreds ofcasual users, who ranged from young children to adults.
958169
Third-Order Moments of Filtered Speech Signals for Robust Speech Recognition
Novel speech features calculated from third-order statistics of subband-filtered speech signals are introduced and studied for robust speech recognition. These features have the potential to capture nonlinear information not represented by cepstral coefficients. Also, because the features presented in this paper are based on the third-order moments, they may be more immune to Gaussian noise than cepstrals, as Gaussian distributions have zero third-order moments. Experiments on the AURORA2 database studying these features in combination with Mel-frequency cepstral coefficients (MFCC's) are presented, and some improvement over the MFCC-only baseline is shown when clean speech is used for training, though the same improvement is not seen when multi-condition training data is used.
62761494
Evolving visual routines
Traditional machine vision assumes that the vision system recovers a complete, labeled description of the world [10]. Recently, several researchers have criticized this model and proposed an alternative model that considers perception as a distributed collection of task-specific, context-driven visual routines [1, 12]. Some of these researchers have argued that in natural living systems these visual routines are the product of natural selection [11]. So far, researchers have hand-coded task-specific visual routines for actual implementations (e.g., [3]). In this article we propose an alternative approach in which visual routines for simple tasks are created using an artificial evolution approach. We present results from a series of runs on actual camera images, in which simple routines were evolved using genetic programming techniques [7]. The results obtained are promising: The evolved routines are able to process correctly up to 93% of the test images, which is better than any algorithm we were able to write by hand.
7686593
Standard tableaux and Klyachko's theorem on Lie representations
We show that for all but two partitions @l of n>6 there exists a standard tableau of shape @l with major index coprime to n. In conjunction with a deep result of Kraskiewicz and Weyman this provides a new purely combinatorial proof of Klyachko's famous theorem on Lie representations of the general linear group.
18721179
Some requirements for architectural support of software debugging
Architectural support of high-level, symbolic debugging is described at three levels of abstraction: the user's view of desired debugging functionality, the debugger implementor's view of architectural requirements that support the functionality, and the computer architect's view of architectural features or attributes that implement the requirements. References are made where possible to computing systems that meet the requirements. The paper is written from the viewpoint of debugger implementors, and is addressed primarily to computer architects.