Very-low-frequency (VLF) (3–30 kHz) radio waves can propagate large distances around the globe in the Earth-ionosphere waveguide and be scattered by transient disturbances to the lower ionosphere. Such scattering enables the VLF remote sensing of lightning-related (as well as other) disturbances to the D-region ionosphere (60–100-km altitude). Indeed, recent work studying the polarization of VLF radio waves has yielded insights into the physical mechanisms associated with “large” early/fast VLF events, which are produced by powerful lightning discharges. While the polarization of the ambient VLF field has been investigated in such cases, the polarization of the field scattered by the ionospheric disturbance has not been investigated in detail, primarily because it can be difficult to measure. In this article, we present a simple, reliable method to accurately calculate the polarization of such a scattered field, and we apply the method to analyze three different types of ionospheric VLF scattering events: an early/fast VLF event, a long-recovery early VLF event, and a lighting-induced electron precipitation (LEP) event. In so doing, we demonstrate the significant advances in VLF remote sensing capabilities provided by the scattered field polarization method.

Satellite and airborne radars currently monitor agricultural regions on Earth. Corn is a globally important crop that may benefit from radar observations for estimating soil moisture (SM) and other quantities. Estimates of SM could be used to enhance crop yield and aid in weather prediction. A scattering model is needed, however, to accurately estimate these quantities. Historically, corn is a difficult crop to model at microwave frequencies, and only approximate models for it exist. Novel models based on full-wave electromagnetic solvers can be more accurate by accounting for multiple scattering among plant constituents, other adjacent plants, and the underlying soil surface. Such a model is computationally expensive, but the increased availability of computing resources may make it more feasible. This article presents a model for corn at L-band based on finite element method (FEM) simulations in conjunction with Monte Carlo methods to estimate polarimetric backscattering coefficients. The FEM simulation uses periodic boundary conditions to limit its size. The physical representation of the corn plants comes from data-based 3-D plant models. The results of simulations are validated with synthetic aperture radar (SAR) data obtained during the SM active passive validation experiment of 2012 (SMAPVEX12) experimental campaign. The estimated backscattering coefficients of the SAR data are within ±2 dB for all polarization channels. Validation is performed for two days within the experimental campaign. Good agreement is observed between the simulated and measured values. This result indicates that the model can give novel insights into the scattering characteristics of corn. Future work remains to build an invertible model for estimating SM from backscatter measurements.

Early/fast very low frequency (VLF) events evidence the direct impulsive coupling of lightning energy to the overlying mesosphere and lower ionosphere, and they are readily detected as rapid (10 dB). Large (>6 dB) early/fast events have not yet been satisfactorily simulated, and past work has suggested that large amplitude early/fast VLF events may only be detected when the receiver is located in a VLF propagation “null.” VLF propagation “nulls” result from the destructive interference of propagating waveguide modes, and they would result in deceptively large relative changes in field amplitude by reducing the magnitude of the ambient field, rather than by increasing the magnitude of the scattered field. In this paper, we present a new method to quantify the degree of destructive modal interference at the location of the VLF receiver, and we apply this method to analyze the impact of modal interference on the detected amplitude changes associated with 235 early/fast VLF events occurring over the Midwestern United States on 21 September 2016. No meaningful dependence on destructive modal interference is detected. We conclude that contemporary models of lightning-ionosphere interactions and/or VLF scattering require modification in order to accurately reproduce observations of large early/fast VLF events.

Whistler mode waves are a type of electromagnetic plasma wave and play a dominant role in the energy dynamics of the near-earth space environment and associated space weather processes. Ground-based observations of these waves are important for numerical model validation, space weather monitoring, and discovery science. Unfortunately, ground-based observations are often challenging to interpret since information about traversal through the ionosphere and distance propagated in the earth-ionosphere waveguide is rarely available. A new approach to identifying the ionospheric exit points of the magnetospheric whistler mode emissions is presented, which takes into account the observed wave polarization. The method relies on the initial circular polarization of the ducted magnetospheric emissions which is shown to convert to linear polarization after propagation in the earth-ionosphere waveguide at a predictable rate. Finite-difference time domain modeling of observed eccentricity provides a metric for determining distance from observer to ionospheric exit point. The method is shown to produce good agreement with observations of magnetospheric chorus emissions, artificially triggered emissions, and lightning-induced whistlers.

For many years, statistical machine translation relied on generative models to provide bilingual word alignments. In 2005, several independent efforts showed that discriminative models could be used to enhance or replace the standard generative approach. Building on this work, we demonstrate substantial improvement in word-alignment accuracy, partly though improved training methods, but predominantly through selection of more and better features. Our best model produces the lowest alignment error rate yet reported on Canadian Hansards bilingual data.

We investigate a number of simple methods for improving the word-alignment accuracy of IBM Model 1. We demonstrate reduction in alignment error rate of approximately 30% resulting from (1) giving extra weight to the probability of alignment to the null word, (2) smoothing probability estimates for rare words, and (3) using a simple heuristic estimation method to initialize, or replace, EM training of model parameters.

We show that it is possible to learn the contexts for linguistic operations which map a semantic representation to a surface syntactic tree in sentence realization with high accuracy. We cast the problem of learning the contexts for the linguistic operations as classification tasks, and apply straightforward machine learning techniques, such as decision tree learning. The training data consist of linguistic features extracted from syntactic and semantic representations produced by a linguistic analysis system. The target features are extracted from links to surface syntax trees. Our evidence consists of four examples from the German sentence realization system code-named Amalgam: case assignment, assignment of verb position features, extraposition, and syntactic aggregation.

This paper presents a method for incorporating word pronunciation information in a noisy channel model for spelling correction. The proposed method builds an explicit error model for word pronunciations. By modeling pronunciation similarities between words we achieve a substantial performance improvement over the previous best performing models for spelling correction.

The noisy channel model has been applied to a wide range of problems, including spelling correction. These models consist of two components: a source model and a channel model. Very little research has gone into improving the channel model for spelling correction. This paper describes a new channel model for spelling correction, based on generic string to string edits. Using this model gives significant performance improvements compared to previously proposed models.

CommandTalk (Moore et al., 1997) is a spokenlanguage interface to the ModSAF battle eld simulator that allows simulation operators to generate and execute military exercises by creating

To achieve widespread acceptance, speech understanding technology needs to be domain independent. Deep understanding, however, appears to require knowledge that is domain specific. Speech understanding technology, therefore, must be partitioned into domain-independent and domain-specific components. Development of domain-independent components could be promoted by creation of semantically annotated corpora. Any such corpus, however, would be difficult to produce and would necessarily be controversial because of lack of widespread agreement on principles of semantic analysis. The use of such a corpus for performance evaluation should therefore be left largely up to the research community rather than being imposed by funding agencies.

We describe an efficient bottom-up parser that interleaves syntactic and semantic structure building. Two techniques are presented for reducing search by reducing local ambiguity: Limited left context constraints are used to reduce local syntactic ambiguity, and deferred sortal-constraint application is used to reduce local semantic ambiguity. We experimentally evaluate these techniques, and show dramatic reductions in both number of chart edges and total parsing time. The robust processing capabilities of the parser are demonstrated in its use in improving the accuracy of a speech recognizer.

Article Free Access Share on Gemini: a natural language system for spoken-language understanding Authors: John Dowding SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , Jean Mark Gawron SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , Doug Appelt SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , John Bear SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , Lynn Cherny SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , Robert Moore SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile , Douglas Moran SRI International, Menlo Park, CA SRI International, Menlo Park, CAView Profile Authors Info & Claims ACL '93: Proceedings of the 31st annual meeting on Association for Computational LinguisticsJune 1993Pages 54–61https://doi.org/10.3115/981574.981582Published:22 June 1993Publication History 43citation1,076DownloadsMetricsTotal Citations43Total Downloads1,076Last 12 Months25Last 6 weeks7 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Publisher SiteeReaderPDF

An approach to implementing spoken language systems is discussed. This approach takes full advantage of syntactic and semantic constraints provided by a natural language processing component in the speed understanding task and provides a tractable search space. The results indicate that the approach is a promising one for large-vocabulary spoken language systems. Parse times within a factor of 20 of real time are achieved for high-perplexity syntactic grammars with resulting hidden Markov model recognition computational requirements (2500 active words/frame) that are well within the capability of high-speed multiprocessor computers or special-purpose speech recognition hardware.>

We show how unification can be used to specify the semantic interpretation of natural-language expressions, including problematical constructions involving long-distance dependencies. We also sketch a theoretical foundation for unification-based semantic interpretation, and compare the unification-based approach with more conventional techniques based on the lambda calculus.

We present an algorithm for generating strings from logical form encodings that improves upon previous algorithms in that it places fewer restrictions on the class of grammars to which it is applicable. In particular, unlike an Earley deduction generator (Shieber, 1988), it allows use of semantically nonmonotonic grammars, yet unlike topdown methods, it also permits left-recursion. The enabling design feature of the algorithm is its implicit traversal of the analysis tree for the string being generated in a semantic-head-driven fashion.

No abstract available.

Most current theories of natural-language processing propose that the assimilation of an utterance involves producing an expression or structure that in some sense represents the literal meaning of the utterance. It is often maintained that understanding what an utterance literally means consists in being able to recover such a representation. In philosophy and linguistics this sort of representation is usually said to display the "logical form" of an utterance. This paper surveys some of the key problems that arise in defining a system of representation for the logical forms of English sentences and suggests possible approaches to their solution. The author first looks at some general issues relating to the notion of logical form, explaining why it makes sense to define such a notion only for sentences in context, not in isolation, and then discusses the relationship between research on logical form and work on knowledge representation in artificial intelligence. The rest of the paper is devoted to examining specific problems in logical form. These include the following: quantifiers; events, actions and processes; time and space; collective entities and substances; propositional attitudes and modalities; and questions and imperatives.

This paper describes D-Script, a language for representing knowledge in artificial intelligence (AI) programs. D-Script contains a powerful formalism for descriptions, which permits the representation of statements that are problematical for other systems. Particular attention is paid to problems of opaque contexts, time contexts, and knowledge about knowledge. The design of a deductive system for this language is also considered.