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We set if. (2) Mean.
This we do by extracting the subgraph from our original VSN that contains the nodes from the video as well as all other nodes in the VSN that are connected to the nodes from : we set if and.
with, is phoneme context influence length, depending on the speaking speed and the frame rate of the recorded video, we set, if the frame rate is 50 Hz, at 25 Hz. is set to 0.3. is a phoneme distance matrix with size of, which denotes visual similarities between phoneme pairs. is computed by weighted Euclidean distance in the PCA space: (5).
We set if and only if, where is the estimated adjacency matrix for run number r and is the consensus threshold level for edge acceptance.
Similar(56)
The conclusion follows if we set in part (3).
If we set in Corollary 2.4, then we have [7, Theorem 1].
If we set in Theorem 2.5, then we obtain the following corollary from Theorem 2.5.
In the special case, if we set in (1.2), we have (1.3).
If we set in Lemma 2.1, then we can obtain the following corollary.
If we set in Corollary 2.8, then we have [7, Corollary 1].
If we set in (4.40) and divide by, then we obtain (4.41).
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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