Perhaps it would be a good idea to compare the translated text to the text that the user wants to save.
If they are more than 95% the same, that means that the user didn't take the effort to correct the text.
Cheers, Micru
On Wed, May 3, 2017 at 10:31 AM, Wojciech Pędzich wpedzich@gmail.com wrote:
It does depend a lot on the engagement level of the human behind the keyboard. When I deal with machine-translated text, I simply wonder whether the someone behind the keyboard took efforts to actually read the piece.
Now whether this would work if limited to namespaces outside "main" - I do not want to demonise the issue, but if the person submitting the text for machine translation does not read it, what will stop them from a quick ctrl+c / ctrl+v? Just asking.
Wojciech
W dniu 2017-05-03 o 09:33, Yaroslav Blanter pisze:
Creating machine translations only in the draft space (or in the user space
in the projects which do not have draft) could help.
Cheers Yaroslav
On Tue, May 2, 2017 at 10:16 PM, Pharos pharosofalexandria@gmail.com wrote:
I think it all depends on the level of engagement of the human translator.
When the tool is used in the right way, it is a fantastic tool.
Maybe we can find better methods to nudge people toward taking their time and really doing work on their translations.
Thanks, Pharos
On Tue, May 2, 2017 at 4:09 PM, Bodhisattwa Mandal < bodhisattwa.rgkmc@gmail.com> wrote:
Content translation with Yandex is also a problem in Bengali Wikipedia.
Some users have grown a tendency to create machine translated meaningless articles with this extension to increase edit count and article count.
This
has increased the workloads of admins to find and delete those articles.
Yandex is not ready for many languages and it is better to shut it. We don't need it in Bengali.
Regards On May 3, 2017 12:17 AM, "John Erling Blad" jeblad@gmail.com wrote:
Actually this _is_ about turning ContentTranslation off, that is what
several users in the community want. They block people using the
extension
and delete the translated articles. Use of ContentTranslation has
become
a
rather contentious case.
Yandex as a general translation engine to be able to read some alien language is quite good, but as an engine to produce written text it is
not
very good at all. In fact it often creates quite horrible Norwegian,
even
for closely related languages. One quite common problem is reordering
of
words into meaningless constructs, an other problem is reordering
lexical
gender in weird ways. The English preposition "a" is often translated
as
"en" in a propositional phrase, and then the gender is added to the
following phrase. That gives a translation of "Oppland is a county
in…"
into something like "Oppland er en fylket i…" This should be "Oppland
er
et fylke i…".
(I just checked and it seems like Yandex messes up a lot less now than previously, but it is still pretty bad.)
Apertium works because the language is closely related, Yandex does not work because it is used between very different languages. People try to
use
Yandex and gets disappointed, and falsely conclude that all language translations are equally weird. They are not, but Yandex translations
are
weird.
The numerical threshold does not work. The reason is simple, the number
of
fixes depends on language constructs that fails, and that is simply
not a
constant for small text fragments. Perhaps if we could flag specific
language constructs that is known to give a high percentage of
failures,
and if the translator must check those sentences. One such language
construct is disappearances between the preposition and the gender of
the
following term in a prepositional phrase. If they are not similar, then
the
sentence must be checked. It is not always wrong to write "en jenta" in Norwegian, but it is likely to be wrong.
A language model could be a statistical model for the language itself,
not
for the translation into that language. We don't want a perfect
language
model, but a sufficient language model to mark weird constructs. A very
simple solution could simply be to mark tri-grams that does not
already
exist in the text base for the destination as possible errors. It is
not
necessary to do a live check, but at least do it before the page can
be
saved.
Note the difference in what Yandex do and what we want to achieve;
Yandex
translates a text between two different languages, without any clear
reason
why. It is not to important if there are weird constructs in the text,
as
long as it is usable in "some" context. We translate a text for the
purpose
of republishing it. The text should be usable and easily readable in
that
language.
On Tue, May 2, 2017 at 7:07 PM, Amir E. Aharoni < amir.aharoni@mail.huji.ac.il> wrote:
2017-05-02 18:20 GMT+03:00 John Erling Blad jeblad@gmail.com:
Brute force solution; turn the ContentTranslation off. Really > stupid
solution.
>
... Then I guess you don't mind that I'm changing the thread name :)
The next solution; turn the Yandex engine off. That would solve a > part of the problem. Kind of lousy solution though. > > What about adding a language model that warns when the language > constructs
> gets to weird? It is like a "test" for the translation. The CT is > used
for
> creating a translation, but the language model is used for > verifying
if
the
> translation is good enough. If it does not validate against the > language
model it should simply not be published to the main name space. It > will
still be possible to create a draft, but then the user is
> completely
aware
> that the translation isn't good enough. > > Such a language model should be available as a test for any > article,
as
it
> can be used as a quality measure for the article. It is really a > quantity
measure for the well-spokenness of the article, but that isn't > quite
so
intuitive.
> > So, I'll allow myself to guess that you are talking about one
particular
language, probably Norwegian.
Several technical facts:
- In the past there were several cases in which translators to
different
languages who reported common translation mistakes to me. I passed
them
on
to Yandex developers, with whom I communicate quite regularly. They acknowledged receiving all of them. I am aware of at least one such
common
mistake that was fixed; possibly there were more. If you can give me
a
list
of such mistakes for Norwegian, I'll be very happy to pass them on. I absolutely cannot promise that they will be fixed upstream, but it's possible.
- In Norwegian, Apertium is used for translating between the two
varieties
of Norwegian itself (Bokmål and Nynorsk), and from other Scandinavian languages. That's probably why it works so well—they are similar in grammar, vocabulary, and narrative style (I'll pass it on to Apertium developers—I'm sure they'll be happy to hear it). Unfortunately,
machine
translation from English is not available in Apertium. Apertium works
best
with very similar languages, and English has two characteristics,
which
are
unfortunate when combined: it is both the most popular source for translation into almost all other languages (including Norwegian),
and
it
is not _very_ similar to any other languages (except maybe Scots).
Machine
translation from English into Norwegian is only possible with Yandex
at
the
moment. More engines may be added in the future, but at the moment
that's
all we have. That's why disabling Yandex completely would indeed be a
lousy
solution: A lot of people say that without machine translation
integration
Content Translation is useless. Not all users think like that, but
many
do.
- We can define a numerical threshold of acceptable percentage of
machine
translation post-editing. Currently it's 75%. It's a tad
embarrassing,
but
it's hard-coded at the moment, but it can be very easily be made
into a
variable per language. If the translator tries to publish a page in
which
less than that is modified, a warning will be shown.
- I'm not sure what do you mean by "language model". If it's any
kind
of a
linguistic engine, then it's definitely not within the resources that
the
Language team itself can currently dedicate. However, if somebody who
knows
Norwegian and some programming will write a script that analyzes
common
bad
constructs in a Wikipedia dump, this will be very useful. This would basically be an upgraded version of suggestion #1 above. (In my spare
time
as a volunteer I'm doing something comparable for Hebrew, although
not
for
translation, but for improving how MediaWiki link trails work.) _______________________________________________ Wikimedia-l mailing list, guidelines at: https://meta.wikimedia.org/ wiki/Mailing_lists/Guidelines and https://meta.wikimedia.org/ wiki/Wikimedia-l New messages to: Wikimedia-l@lists.wikimedia.org Unsubscribe: https://lists.wikimedia.org/
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