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As a result, the distance between the mean vectors of adjacent states can be large.
In this article, speaker adaptation is performed by updating the mean vectors of the output distribution of an HMM.
In order to adapt mean vectors of the SI model, the MAP adaptation process is composed of two major stages.
A GMM supervector is formed by concatenating the mean vectors of GMM mixture components into a single vector.
Section 2.3 explains the probabilistic 2-mode analysis of a set of mean vectors of training HMMs.
It is commonly believed that the mean vectors of GMMs represent the most characteristics of speakers [1], which are obtained by using the maximum a posteriori (MAP) adaptation.
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LEYLA ISIK: For each sensor, so that it correlates the vector of sensor activity with the mean vector of sensor activities for each class.
The local mean-based k-nearest neighbor classifier (LMKNN) was firstly introduced to achieve robustness against outliers by computing the local mean vector of k nearest neighbors for each class.
Moreover, when the object is to detect small shifts in the mean vector of a process, the performance of Cumulative Sum (CUSUM) control charts is dramatically better than Schewhart control charts.
Here we denote the mean vector of Class1 as μ1 and the mean vector of Class2 as μ2.
where ( {overline{mathbf{x}}}_i )is the mean vector of ith class' training samples, and ( overline{mathbf{x}} ) is the mean vector of total training samples.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com