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In model adaptation, the trained acoustic models of a speech recognizer are adapted to be acoustically matched into the test environment.
In the HEQ-based model adaptation, the HEQ and proposed variance adaptation techniques are applied to the 39-dimensional mean vectors and diagonal covariance matrices, respectively, of all trained HMMs in the baseline speech recognizers on a component-by-component basis.
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The experimental results also indicate that the mean model adaptation plays the major role in improving the performance of the speech recognizer in noisy environments.
One is through the model adaptation approaches, which adapt the clean model towards the distorted speech features.
The variable forgetting factor recursive least squares (VFF-RLS) algorithm was selected to capture the dynamics of the process online for the purpose of model adaptation in the controller.
Reverberant speech recognition has been tackled by feature enhancement at the front-end and model adaptation at the back-end.
Hence, to model adaptation to the stimulus tank background in fullspectrum light the corresponding quantal catch rates were fixed, which means that all cones were equally stimulated.
Basically, the model adaptation approach needs to adapt the entire model parameters employed in the speech recognizer.
Also, we introduce a general model adaptation of the steady diffusion equation for extremely anisotropic diffusion problems with closed field lines.
model adaptation requires the amount of S × D t + S E × D a, (2).
In this model, adaptation reduces the negative effect of pollution on GDP.
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