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One silent segment scrolls through a visual alphabet of iconic femininity, and the ending explodes into Petronian ecstasy, with additional intoxication provided by a Nico Muhly recording.
If noise estimation only be updated in the silent segment, the delay may be as long as 2 s.
Finally, UMVAD will adopt different strategies in the silent segment and speech segment by making a decision between VAD-based and MMSE-based noise estimation.
In silent segment, since the SNRs are different at different frequency points and the accuracy of VAD result is unsatisfying, in order to improve the accuracy of VAD, we classify all the frequency points into two categories further according to Eq. (25), and different strategies are taken on each of the two categories.
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Significantly, these silent segments correspond with areas that have produced very energetic earthquakes in the historic and prehistoric past — the antecedents of what Californians refer to, with dread and some bravado, as the Big One.
Unlike most music signals, silent segments commonly occur in speech utterances.
The insertion of watermark bits into silent segments would render them vulnerable to noise perturbation and susceptible to attacks through the simple removal of silence.
Firstly, the input noisy speech signals are classified into two categories: silent segments and speech segments according to the modified VAD based on the adaptive threshold described in Section 3.2.1.
As Fig. 6 shows, by using an adaptive threshold, the result of VAD (denoted by the red line) can find many silent segments that cannot be detected when a fixed threshold is used.
However, most of these methods depend on an accurate estimate of the noise power spectrum, for example, estimation of the noise magnitude spectrum during silent segments in [3], or a priori signal-to-noise ratio (SNR) estimation in [9], or estimation of the noise covariance matrix in the subspace-based methods.
In the original, a picture caption accompanying the Silent Witness segment erroneously stated that Tom Ward was pictured.
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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