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In VC, the source dictionary is constructed using sufficient source speaker data, and it is adapted using a small amount of parallel data (about ten words only) in order to obtain the target dictionary, where a linear regression transformation matrix (affine matrix) is trained based on NMF.
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This phone confusion matrix was trained on the training data employed for acoustic model training by running a phone recognition experiment.
Since the weights of the matrix are trained with strict image prior constraint, the convolution layer whose parameters are transferred from the well-trained matrix has took the image prior into account.
As depicted in Fig. 2, to evolve the Bayes kernel, a new post probability matrix was trained to replace the old one with the labeled samples from the changed production line.
The weight matrix was trained with a self-organizing map algorithm in the Finnish SOM Toolbox (http://www.cis.hut.fi/projects/somtoolbox/) using a melody that systematically moved through all the major and minor keys in Western tonal music (Janata, Birk, et al. 2002; Janata et al. 2003).
The matrix A is trained by using the dataset shown in Section 5, and the matrix A is contained of the eigenvectors of Equation (7).
This is different from that in (7), where the matrix D is trained from a dataset using the EM algorithm in a manner similar to the matrix T for the i-vector.
A matrix of architectures is trained, varying the numbers of inputs and neurons, and the architecture that provides the best, statistically significant performance is selected as the final model.
A machine learning model is trained on this matrix.
This is my tour guide, Mark, who is trained in both matrix energetics AND reconnection therapy.
A regression algorithm is trained on these matrices to produce a model that can reproduce the targets (with minimum error) given the input vectors from the 2D matrix.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com