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The labels are indecipherable, the nomenclature is confusing, and the language, for non-German speakers, is difficult to translate.
While we've been told for some time now that finding female speakers is difficult, last week I helped put on a conference (in tech, the male-est domain of all), and I can confirm that it's not the case.
The problem of tracking multiple intermittently speaking speakers is difficult as some distinct problems must be addressed.
Counting the number of ASL speakers is difficult because ASL users have never been counted by the American census.
Similar(56)
The spoken lines are disembodied, delivered in voice-over (in Spanish; the show has English supertitles) so their identification with the speaker is difficult if not purposely obscured.
Audio localization for a single active speaker is difficult because human speech is an intermittent signal and contains much of its energy in the low-frequency bins where spatial discrimination is imprecise.
However, the current simulations based on the breathing-sound power spectra, and the human-psychophysical experiments, suggest that speaker recognition is difficult with purely unvoiced sounds.
Applying a cutoff criterion based on a difference in absolute rates to distinguish fluent speakers and stutterers is difficult.
Such a text is for Czech native speakers understandable but it is difficult for computational processing.
While positioning your speakers at an exact angle is difficult to do, anyone can eyeball an angle of roughly 60 degrees.
The voice on the tape recording is squeaky and excitable, the speaker using such a strong dialect that it is difficult even for native Korean speakers to understand.
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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