This paper describes a new criterion of speech recognition using an integrated confidence measure for minimization of the word error rate (WER). Conventional criteria for WER minimization obtain an expected WER of a sentence hypothesis merely by comparing it with other hypotheses in an n-best list. The proposed criterion estimates the expected WER by using an integrated confidence measure with word posterior probabilities for a given acoustic input. The integrated confidence measure, which is implemented as a classifier based on maximum entropy (ME) modeling, is used to get probabilities reflecting whether the word hypotheses are correct or incorrect. The classifier comprises a variety of confidence measures and can deal with a temporal sequence of them in order to attain a more reliable confidence. Our proposed criterion achieved a WER of 7.5% and a 2.6% improvement relative to conventional n-best rescoring methods in transcribing Japanese broadcast news under noisy field and spontaneous speech conditions.
3D coseismic deformation detected by remote sensing yields essential information for estimating the geometry and slip distribution of the causative fault. However, it is often difficult to be obtained by a single observation method due to data acquisition constraints. This study constructs a 3D coseismic deformation model of the 2011 Fukushima-ken Hamadori earthquake by integrating Differential Interferometric Synthetic Aperture Radar (DInSAR), and differential light detection and ranging (Dlidar) analyses. Both horizontal and vertical movements observed are almost consistent with those of the theoretical dislocation model of normal faulting. The fault displacements measured within ±45 m of the rupture based on the 3D deformation model is also in good agreement with the possible maximum field displacements. Fault dips and lateral displacement components are also harmonious with the field survey measurements. Dlidar detects full 3D motion, whereas the DInSAR detects deformations too small for the light detection and ranging (lidar). Combining the two products is helpful to produce a more robust 3D displacement field than possible from the lidar alone.
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