One speaker, who sounded like they were from the mid-west United States, was dropping the S off words in a couple clips. I wasn't sure if it was misreads or some accent I'd never heard.
Another speaker, with a thick accent that sounded European, sounded out all the vowels in circuit. Had I not had the line being read, I don't think I'd have understood the word.
I heard a speaker with an Indian accent who added a preposition to the sentence that was inconsequential but incorrect none the less.
I hear these random prepositions added as flourishes frequently with some Indian coworkers, does anyone know the a reason? It's kind of like how American's interject "Umm..." or drop prepositions (e.g. "Are you done your meal?") and I almost didn't pick up on it. For that matter where did the American habit of dropping prepositions come from? It seems like it's people in the North East primarily.
[¹] If that's even fair given it's a dialect in its own right - Americans also say things differently than I would as a 'Britisher'
I'd say it's mostly subtler (I suppose that should be the expected distribution!) things I've noticed though, they're just harder to recall as a result.
(Just want to emphasise I'm not making fun of anybody or saying anything's wrong, in case it's not clear in text. I'm just enjoying learning Hindi, fairly interested in language generally, and interested/amused to notice these things.)
Hindi is much more economical, to put it literally, one says things like 'than/from/compared to orange, lemon is sour', and 'orange is little/less [without comparison] sour'.
Which, I believe, is what gives rise to InE sentences like 'the salt in this is very less' (it needs more salt, there's very little).
[1] https://f-droid.org/packages/org.commonvoice.saverio/
[2] https://discourse.mozilla.org/t/discussion-of-new-guidelines...
(The first clip I got was spoken more or less correctly, but a couple of words are slurred together and the prosody is awkward. Without having a good idea of the standards and goals of the project, I have no idea whether including this clip would make the overall dataset better or worse. My gut feeling is that it's good for training recognition, and bad for training synthesis.)
This seems to me like a major issue, since it should take a relatively small amount of effort to write up a list of guidelines, and it would be hugely beneficial to establish those guidelines before asking a lot of volunteers to donate their time. I don't find it encouraging that this has been an open issue for four years, with apparently no action except a bunch of bikeshedding: https://github.com/common-voice/common-voice/issues/273