Learning Fault-tolerant Speech Parsing with SCREEN

This paper describes a new approach and a system SCREEN for fault-tolerant speech parsing. SCREEEN stands for Symbolic Connectionist Robust EnterprisE for Natural language. Speech parsing describes the syntactic and semantic analysis of spontaneous spoken language. The general approach is based on incremental immediate flat analysis, learning of syntactic and semantic speech parsing, parallel integration of current hypotheses, and the consideration of various forms of speech related errors. The goal for this approach is to explore the parallel interactions between various knowledge sources for learning incremental fault-tolerant speech parsing. This approach is examined in a system SCREEN using various hybrid connectionist techniques. Hybrid connectionist techniques are examined because of their promising properties of inherent fault tolerance, learning, gradedness and parallel constraint integration. The input for SCREEN is hypotheses about recognized words of a spoken utterance potentially analyzed by a speech system, the output is hypotheses about the flat syntactic and semantic analysis of the utterance. In this paper we focus on the general approach, the overall architecture, and examples for learning flat syntactic speech parsing. Different from most other speech language architectures SCREEN emphasizes an interactive rather than an autonomous position, learning rather than encoding, flat analysis rather than in-depth analysis, and fault-tolerant processing of phonetic, syntactic and semantic knowledge.Comment: 6 pages, postscript, compressed, uuencoded to appear in Proceedings of AAAI 9

SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks

In this paper, we describe a so-called screening approach for learning robust processing of spontaneously spoken language. A screening approach is a flat analysis which uses shallow sequences of category representations for analyzing an utterance at various syntactic, semantic and dialog levels. Rather than using a deeply structured symbolic analysis, we use a flat connectionist analysis. This screening approach aims at supporting speech and language processing by using (1) data-driven learning and (2) robustness of connectionist networks. In order to test this approach, we have developed the SCREEN system which is based on this new robust, learned and flat analysis. In this paper, we focus on a detailed description of SCREEN's architecture, the flat syntactic and semantic analysis, the interaction with a speech recognizer, and a detailed evaluation analysis of the robustness under the influence of noisy or incomplete input. The main result of this paper is that flat representations allow more robust processing of spontaneous spoken language than deeply structured representations. In particular, we show how the fault-tolerance and learning capability of connectionist networks can support a flat analysis for providing more robust spoken-language processing within an overall hybrid symbolic/connectionist framework.Comment: 51 pages, Postscript. To be published in Journal of Artificial Intelligence Research 6(1), 199

Impact of Rotation-Driven Particle Repopulation on the Thermal Evolution of Pulsars

Driven by the loss of energy, isolated rotating neutron stars (pulsars) are gradually slowing down to lower frequencies, which increases the tremendous compression of the matter inside of them. This increase in compression changes both the global properties of rotating neutron stars as well as their hadronic core compositions. Both effects may register themselves observationally in the thermal evolution of such stars, as demonstrated in this Letter. The rotation-driven particle process which we consider here is the direct Urca (DU) process, which is known to become operative in neutron stars if the number of protons in the stellar core exceeds a critical limit of around 11% to 15%. We find that neutron stars spinning down from moderately high rotation rates of a few hundred Hertz may be creating just the right conditions where the DU process becomes operative, leading to an observable effect (enhanced cooling) in the temperature evolution of such neutron stars. As it turns out, the rotation-driven DU process could explain the unusual temperature evolution observed for the neutron star in Cas A, provided the mass of this neutron star lies in the range of 1.5 to 1.9 \msun and its rotational frequency at birth was between 40 (400 Hz) and 70% (800 Hz) of the Kepler (mass shedding) frequency, respectively.Comment: Revised version, 7 pages 4 figures. To appear in Physics Letters

Time parameters and Lorentz transformations of relativistic stochastic processes

Rules for the transformation of time parameters in relativistic Langevin equations are derived and discussed. In particular, it is shown that, if a coordinate-time parameterized process approaches the relativistic Juttner-Maxwell distribution, the associated proper-time parameterized process converges to a modified momentum distribution, differing by a factor proportional to the inverse energy.Comment: 5 pages, 1 figur

Sample path large deviations for Laplacian models in (1+1)(1+1)-dimensions

For Laplacian models in dimension $(1+1)$ we derive sample path large deviations for the profile height function, that is, we study scaling limits of Gaussian integrated random walks and Gaussian integrated random walk bridges perturbed by an attractive force towards the zero-level, called pinning. We study in particular the regime when the rate functions of the corresponding large deviation principles admit more than one minimiser, in our models either two, three, or five minimiser depending on the pinning strength and the boundary conditions. This study complements corresponding large deviation results for gradient systems with pinning for Gaussian random walk bridges in $(1+1)$-dimension (\cite{FS04}) and in $(1+d)$-dimension (\cite{BFO}), and recently in higher dimensions in \cite{BCF}. In particular it turns out that the Laplacian cases, i.e., integrated random walks, show richer and more complex structures of the minimiser of the rate functions which are linked to different phases.Comment: 37, 5 figure

Crystal structure of barium oxonitridophosphate, Ba3P6O6N8

Ba3N8O6P6, trigonal, P3 (no. 147), a = 7.40227(9) Å, c = 6.3144(1) Å, V = 299.6 Å3, Z = 1, R(I) = 0.008, R(P) = 0.041, T = 297(2) K