[wayland-protocols] text-input: Add v3 of the text-input protocol
Weng Xuetian
wengxt at gmail.com
Wed Apr 11 18:52:14 UTC 2018
(forgot to reply to the list)
On Wednesday, 11 April 2018 11:35:58 PDT Dorota Czaplejewicz wrote:
> On Wed, 11 Apr 2018 11:26:22 -0700
>
> Weng Xuetian <wengxt at gmail.com> wrote:
> > On Monday, 9 April 2018 07:20:53 PDT Dorota Czaplejewicz wrote:
> > > On Sun, 11 Mar 2018 20:30:14 +0100
> > >
> > > Carlos Garnacho <carlosg at gnome.org> wrote:
> > > > This new protocol description is a vast simplification over v2,
> > > > highlights
> > > > are:
> > > > - All pre-edit text styling is gone, the protocol doesn't seem the
> > > > place
> > > >
> > > > to convey UI state. Clients are in better knowledge of how to make
> > > > the
> > > > pre-edit string distinguishable from regular text.
> >
> > As an long-time input method developer and CJK user, I'd prefer to keep
> > the
> > styling. In Chinese or Japanese, partially converted text are common and
> > styling is useful to help user to distinguish which text is currently
> > being
> > converted. [1] But for the sake of in-app consistency, I'd say we don't
> > need that much capability about styling though. Among all input methods
> > supported by fcitx [2], only underline/highlight is being commonly used.
> > Recently I started to use some strike style in only one single input
> > method though, it can also be useful in certain cases.
>
> I think this use case is covered. For indicating what's currently being
> changed, this protocol is using "preedit string". In GTK, the preedit text
> is displayed with an underline, making is always clear what the suggestion
> pertains to.
I think you can take a closer look at [1].
"葵あ" is the complete preedit text. The input method is converting "葵" and
giving the candidates for it, the あ part is not yet handled by input method
(but typed by user and appears in the preedit). That's why "葵" is being
highlighted.
In a single CJK text composition, CJK people would type the full sentence
ahead instead of word by word because this helps input method to understand
the whole context and improve the prediction.
[1] https://i.imgur.com/MpibNVi.png
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