6,398 research outputs found
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
Measures of Systemic Risk
Systemic risk refers to the risk that the financial system is susceptible to
failures due to the characteristics of the system itself. The tremendous cost
of systemic risk requires the design and implementation of tools for the
efficient macroprudential regulation of financial institutions. The current
paper proposes a novel approach to measuring systemic risk.
Key to our construction is a rigorous derivation of systemic risk measures
from the structure of the underlying system and the objectives of a financial
regulator. The suggested systemic risk measures express systemic risk in terms
of capital endowments of the financial firms. Their definition requires two
ingredients: a cash flow or value model that assigns to the capital allocations
of the entities in the system a relevant stochastic outcome; and an
acceptability criterion, i.e. a set of random outcomes that are acceptable to a
regulatory authority. Systemic risk is measured by the set of allocations of
additional capital that lead to acceptable outcomes. We explain the conceptual
framework and the definition of systemic risk measures, provide an algorithm
for their computation, and illustrate their application in numerical case
studies.
Many systemic risk measures in the literature can be viewed as the minimal
amount of capital that is needed to make the system acceptable after
aggregating individual risks, hence quantify the costs of a bail-out. In
contrast, our approach emphasizes operational systemic risk measures that
include both ex post bailout costs as well as ex ante capital requirements and
may be used to prevent systemic crises.Comment: 35 pages, 11 figure
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 -dimensions
For Laplacian models in dimension 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 -dimension (\cite{FS04}) and in -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) Ă…, c = 6.3144(1) Ă…, V = 299.6 Ă…3, Z = 1, R(I) = 0.008, R(P) = 0.041, T = 297(2) K
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