8,658 research outputs found
Max-margin Metric Learning for Speaker Recognition
Probabilistic linear discriminant analysis (PLDA) is a popular normalization
approach for the i-vector model, and has delivered state-of-the-art performance
in speaker recognition. A potential problem of the PLDA model, however, is that
it essentially assumes Gaussian distributions over speaker vectors, which is
not always true in practice. Additionally, the objective function is not
directly related to the goal of the task, e.g., discriminating true speakers
and imposters. In this paper, we propose a max-margin metric learning approach
to solve the problems. It learns a linear transform with a criterion that the
margin between target and imposter trials are maximized. Experiments conducted
on the SRE08 core test show that compared to PLDA, the new approach can obtain
comparable or even better performance, though the scoring is simply a cosine
computation
Parallel-cascade-based mechanisms for heating solar coronal loops: test against observations
The heating of solar coronal loops is at the center of the problem of coronal
heating. Given that the origin of the fast solar wind has been tracked down to
atmospheric layers with transition region or even chromospheric temperatures,
it is worthy attempting to address whether the mechanisms proposed to provide
the basal heating of the solar wind apply to coronal loops as well. We extend
the loop studies based on a classical parallel-cascade scenario originally
proposed in the solar wind context by considering the effects of loop
expansion, and perform a parametric study to directly contrast the computed
loop densities and electron temperatures with those measured by TRACE and
YOHKOH/SXT. This comparison yields that with the wave amplitudes
observationally constrained by SUMER measurements, while the computed loops may
account for a significant fraction of SXT loops, they seem too hot when
compared with TRACE loops. Lowering the wave amplitudes does not solve this
discrepancy, introducing magnetic twist will make the comparison even less
desirable. We conclude that the nanoflare heating scenario better explains
ultraviolet loops, while turbulence-based steady heating mechanisms may be at
work in heating a fraction of soft X-ray loops.Comment: 6 pages, 1 figure, to appear in proceedings of AstroNum-201
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