We've added a feature in 4.0 that's something like a concordance - lists all of the words in the document. This could be narrowed to the current page, I suppose, or last selected paragraph, or something along those lines - what sort of unit of text would be most useful here?
Some of the Pleco ebooks already have a similar feature, for example in the graded reader series, in which certain advanced vocabulary words/phrases are highlighted.
Purple culture has a convenient tool that, after parsing the provided text, will extract the vocabulary works according to user-defined filters (HSK levels). This sounds similar to what you are describing with the concordance but with a filtering option. In addition to filtering based on HSK, filtering based on "not being in specified flashcard lists" or filtering based on some measure of frequency (should such data be available) would also be nice.
The queue that you describe is an interesting idea, but I'm kind of waiting until we have a better sense of where things are going with iPad (is everyone going to just buy a tiny M1 Mac and call it a day?) - and with tablets in general, with Google now pushing this big new Android tablet revamp for next year - before investing a whole lot more time in adding new iPad-specific features beyond the ones we've already added in 4.0 (mouseover, key control, etc).
That one I'm less clear on - we don't currently define proper nouns, doing that requires a bunch of ML stuff on the back end and our main goal for reader text analysis in 4.0 was simply having it be reasonably accurate + very fast. So we could consider working in a slower algorithm in the future that would do that but I don't know if most people would find the speed tradeoffs worth it.
I recognize this feature of a dedicated pop-up vocabulary area is a bit of a jump from the current implementation of Pleco's reader functionality. Here's a youtube video that somewhat depicts the idea and usage of this feature:
This is the kind of use case I had in mind. For example, after pasting in a chapter of a novel, the user could play the TTS and easily glance over at the vocabulary section when unfamiliar words come up. This feature does not necessarily need a lot of space or be limited to devices with larger screens, though serious learners would likely gravitate to the larger-screen devices.
Pleco is certainly fast. There is some room to improve accuracy with ML processing, but it's understandable that there's always the potential of "opening a can of worms". Still, improved parsing of the text as an option, even if there's a small delay at the start, would be nice. In addition to the improved parsing, the ability to add spaces, as another user recently commented on, would be nice. This spacing feature, for example, is nicely implemented in "The Chairman's Bao" app.
That one I'm less clear on - we don't currently define proper nouns, doing that requires a bunch of ML stuff on the back end and our main goal for reader text analysis in 4.0 was simply having it be reasonably accurate + very fast. So we could consider working in a slower algorithm in the future that would do that but I don't know if most people would find the speed tradeoffs worth it.
Underlining is also a feature that is also a jump from the current implementation of Pleco's reader functionality. Underlining can be particularly helpful when there are many proper nouns in the text, which often comes up when reading text that has been translated into Chinese. Here's a wiki link to some brief text on "Underlines in Chinese":
https://en.wikipedia.org/wiki/Underscore#Underlines_in_Chinese
If such an underlining feature could be implemented, it could be extended to easily spot the more advanced vocabulary words. This vocabulary underlining feature, for example, is implemented in the "Du Chinese" application, though that application does not provide any options for customization.