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Convolutional neural network (CNN) has drawn increasing interest in visual tracking, among which fully-convolutional Siamese network based method (SiamFC) is quite popular due to its competitive performance in both precision and efficiency. Generally, SiamFC captures robust semantics from high-level features in the last layer but ignores detailed spatial features in earlier layers, thus tending to...
In this paper, a pathological voice dataset (PVD) is introduced. The dataset contains recordings of 14 speakers (9 female and 5male) and two health states: normal and unhealthy. Each speaker pronounces fixed words, prompted digits, reads sentences and gives free talking. These materials cover all the phonemes in Chinese. The dataset also considerate the channel variability and is recorded through...
Although the basic method of cognitive reliability and error analysis method (CREAM) is widely used, there are still a lot of problems, for example, there is no consideration of the problems that CPC has different weights in different industrial environments and the process of determining control mode is not smooth. Therefore, the prediction of human error probability (HEP) in the basic method is...
This paper first proposes a simple and effective nonuniform interpolation method and a deblurring method based on back propagation neural networks (BPNN). The proposed non-uniform interpolation method and deblurring method are then coupled to constitute a novel two-step super-resolution algorithm. The simulated results indicate that the proposed two-step super-resolution method shows better results...
Speech with various emotions aggravates the performance of speaker recognition system. The existing speaker modeling disregards the match of the emotional state between training and testing speech, and the systems suffer the lapsus of the emotion recognition as to practical application. We propose an alternative approach that exploits the prosodic difference to cluster affective speech, and then builds...
Speech with various emotions aggravates the performance of speaker recognition systems. In this paper, a novel score normalization approach called pitch envelope based frame level score reweighted (PFLSR) algorithm is introduced to compensate the influence of the affective speech on speaker recognition. The approach assumes that the maximum likelihood model is not easily changed with the expressive...
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