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Because of the inadequate performance of speech recognition systems, an accurate confidence scoring mechanism should be employed to understand user requests correctly. To determine a confidence score for a hypothesis, certain confidence features are combined. The performance of filler-model based confidence features have been investigated. Five types of(More)
The problem of inferring a missing face image which is at much higher resolution from lower observations is called as Face Super Resolution or Hallucination problem. Mostly the problem is approached in spatial domain by using the aligned textural information of the observation. However the ignorance of the shape information limits the performance of these(More)
Increasing the resolution of images by synthesis may cause errorneous results due to the assymetry problem. As stated in assymetry problem, models could not fit the lower resolution inputs due to increased interpolation and noise. In order to avoid this problem RAF (Resolution Aware Fitting) algorithm has been proposed. In this approach no processing has(More)
In face hallucination problem it is critical to synthesize the correct facial details. General tendency is using textural priors either in parametric or non-parametric fashion. Though a certain amount of details could be obtained, limitations in texture priors force the utilization of shape information in addition to texture. As in Resolution Aware Fitting(More)
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