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"Today, because we have been successful in creating a community that extends far beyond our events, people just don't feel as much of a need to show up for every speaker or bar night, and fewer people pay the dues that help us maintain that large infrastructure".
Recordings for every speaker were made during a single session.
Having annotated a large quantity of breaths and filled pauses "yyy" for every speaker (with the latter not appearing only for 2 out of 30 speakers in our corpus), we decided to analyze inter-speaker differences.
The Bayesian information criterion (BIC) is widely employed in many studies as [23] to generate a break-point for every speaker change and environment/channel condition change in the BN domain.
For the parameters which could be obtained for every speaker in our corpus, (i.e., b_p and f_p y) durations), we concluded an analysis of variance (ANOVA) in order to check the statistical significance of differences between speakers based upon only one of these parameters at a time.
Analysis of those plots leads to the conclusion that although the differences are not statistically significant for every speaker pair, it makes sense to group the speakers into 2 or 3 categories, as in: speakers taking short breaths, speakers taking breaths of average length, speakers taking long breaths, and the same for "yyy" fillers.
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(For every native speaker of French, there are about 3 native speakers of Bengali. For every American undergrad studying Bengali, there are about 2,226 American students studying French).
Based on this dataset, we can observe all Tweet-Retweet (TR) events for every monitored Speaker over the course of 10 days, and so we can ask whether a Speaker has gained one or more new followers among the set of Listeners of her retweets.
The first is for every English speaker.
You won't want to listen to your favourite bands with it, but that remains true for every smartphone/phablet speaker.
And before he did that, Yarmuth continued a strategy he had adopted for every Republican speaker that day: reading off data from the Department of Health and Human Services and the Commonwealth Fund on the impact of repealing Obamacare in that Republican's state.
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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