Re: MT Confidence definition [ACTION-556]

Hi all,

I think Yves makes a good point.

In my view, on reviewing the discussions, as it stands MT Confidence can be
used to represent two different types of "confidence" scores. They are very
closely related, but still quite different.

It is worth remembering that the original motivation behind the MT
Confidence category is to provide an automatically-generated value which
offers some information on the perceived quality of a translation produced
by an MT engine. This value can then be used in subsequent processes e.g.
during post-editing processes, during additional more sophisticated quality
estimation processes etc.

   1. The quality score of the translation as produced by an MT engine (for
   the most part this type of score is usually only produce by
   statistical-based engine and usually equates to the probability of that
   translation, given specific models used by the engine).
   2. The quality estimation score (such as provided by the QuEst tool or
   by some additional process).

Both are dependant on the MT engine. The first is produced directly by the
MT engine. The second uses both MT-system-internal features (including
features extracted from internal MT translation and language models as well
as the final translation probability as produced by the MT engine) and
additional external features. This is the reason why MT confidence needs to
additional provide information about the engine (and perhaps in the case of
#2 any additional tools that were used in deriving the MT confidence),
otherwise the number on it's own is hard to interpret and to reuse.

Based on this, I think, therefore, we can safely remove the
self-referential part of the description of MT Confidence to allow to be
used to capture both #1 and #2 above, but, following Dave's point, we would
need to clarify it with examples of best practises for both instances to
make it clear for implementers. It is not the intention of the category to
define how the score is calculated, so I also think it's a good idea to use
annotatorRef to provide further details on the tools and methods used to
generate the MT Confidence, if required.


Declan


On 21 July 2013 15:26, Jörg Schütz <joerg@bioloom.de> wrote:

> Hi Yves, Dave, and all,
>
> As of yet, the definition of MT Confidence restricts its use case to a
> score internally generated by the employed MT engine. If we would allow for
> the specification of the scoring tool then this data category could be
> easily extended to the score generated by an external tool, for example,
> the QuEst application for Moses based MT engines. Probably, such an
> extension would need further information elements like the models and data
> that have been used in the scoring process.
>
> IMO LQI/non-conformance would be less appropriate for a "confidence"
> measure given the list of possible "quality issues" which are more
> linguistically oriented. Even if we would aggregate the different result
> types with a certain weigthing (penalty), what we would get is an
> approximated quality rating, which we have with LQR (on the document
> level), but not a confidence measure in the above sense.
>
> This is an interesting and forward looking discussion which we should
> continue for future versions of ITS.
>
> Cheers -- Jörg
>
>
> On July 20, 2013 at 22:37 (CEST), Yves Savourel wrote:
>
>> Hi Dave, all,
>>
>> If MT Confidence has been design to hold only a self-reported score, then
>> maybe it should stay that way. I just didn't know the
>> reasoning behind the origin of the data category. But IMO it becomes a
>> data category that is going to very rarely used, except for
>> research tools, production tools have rarely access to such measurement
>> as far as I see. But maybe it's a question of time.
>>
>> This said, in the case of QuEst, while I may be wrong, my understanding
>> is that the type of score you get is very comparable to a
>> self-reporting confidence. You will note that I didn't ask to change the
>> meaning of what MT Confidence is reporting, only that we
>> didn't restrict the tool that generate that score to the MT system itself.
>>
>> The other option would be to use LQI/non-conformance? But I have to say
>> that despite the description that sort of backup that
>> notion, the type name and the data category sound rather off to an
>> end-user like me: Localization quality *Issue* are about
>> reporting problems, and I would imagine a (non)-conformance type is about
>> aggregating data and types of errors to come up with an
>> overall score that is more a composite measurement than something close
>> to an MT Confidence.
>>
>> Would localization Quality Rating be better? It is a rating of the
>> quality of the translation with a rather vague definition.
>>
>> Cheers,
>> -yves
>>
>>
>> -----Original Message-----
>> From: Dave Lewis [mailto:dave.lewis@cs.tcd.ie]
>> Sent: Friday, July 19, 2013 7:39 PM
>> To: Yves Savourel; public-multilingualweb-lt@w3.**org<public-multilingualweb-lt@w3.org>
>> Subject: Re: MT Confidence definition [ACTION-556]
>>
>> Hi all
>> I managed to talk to Declan Groves about this yesterday. His view was
>> that the original use case was to enable to confidence score
>> that all statistical MT already generate in selecting the final output to
>> be propagated in an open way. So using other method is
>> some change (a
>> broadening) of the use case.
>>
>> He also saw the danger of confusion by users/implementors if something
>> labelled as a 'confidence score' (which has a certain meaning
>> in NLP
>> circles) might be used to convey quality estimation (QE), which,
>> depending how its done,  has a different sort of significance.
>>
>> We did discuss the option of mtconfidence being used to convey the output
>> of an automated score (e.g. BLEU) that had been integrated
>> into an MT engine. This would be reasonable in use cases where MT engines
>> are being dynamically retrained, but would require
>> relaxing the wording.
>>
>> I also asked questions of some  QE researchers in CNGL and got some
>> interesting clarifications. Certainly QE is being used to
>> provide scores of MT output (i was mistaken about that on the call),
>> often trained on some human annotation collected on the quality
>> of previous translations correlated to the current translation and
>> perhaps other meta data (including the self reported confidence
>> scores) from the MT engine.
>> Certainly there are also occasions where QE operates in a very similar
>> fashion to that intended for non-conformance in  LQI, so I
>> think that remains an option also.
>>
>> So, Yves, you are right that the current definition is limiting to other
>> possible 'scores' representing a confidence in the
>> translation being a 'good' one,  beyond just the MT-engine generated
>> scores.
>>
>> At the same time I have the impression that the technologies for this are
>> still emerging from the lab and don't have the benefit of
>> widely used common platforms and industrial experience that SMT does.
>> Overall this makes it difficult to make any hard and fast
>> statements about what should and should not be used to generate
>> MtConfidence scores right now.
>>
>> So softening that limitation as Yves suggests may be useful in
>> accommodating innovations in this area, but may also open the door to
>> some confusion by users that may impact negatively on the business
>> benefits of interoperation, e.g. a translation client gets a
>> score that they think has a certain significance when in fact it has
>> another.
>>
>> So, if we were to make the changes suggested by Yves, we should accompany
>> it with some best practice work to suggest how the
>> annotatorRef value could be used to inform on the particular method used
>> to generate the mtconfidence score, including some
>> classification encodings, explanations of the different methods and the
>> significance that can be placed on the resulting scores in
>> different situations. My general feeling, perhaps incorrect, is that the
>> current IG membership probably doesn't have the breadth of
>> expertise to provide this best practice. Arle, could this be something
>> that QT-Launchpad could take on?
>>
>> To sum up:
>> 1) the text proposed by yves may relax limits of what can produce
>> mtconfidence score  in a useful way by accommodating different
>> techniques, but also has the potential to cause confusion about the
>> singificance of score produced by different methods. Some of
>> these could anyway be conveyed in the non-compliance in LQI, but not all.
>>
>> 2) it seems very difficult to formulate wording that would constrain the
>> range of methods in any usable way between the current text
>> and what Yves suggests. So let restrict ourselves to these two options.
>>
>> 3) If we relax the wording as Yves suggests, expertise would be needed to
>> form best practice on the use of the annotatorsRef value
>> to provide a way of classifying the different scoring methods in a way
>> that's useful for users.
>>
>> Apologies for the long email, but unfortunately i could find any clear
>> pointers one way or another.  Personally, I'm more neutral
>> the proposal.
>> But also I don't know if we could categorize this as a minor
>> clarification or not either.
>>
>> Please voice your views on the list, and lets try and get consensus
>> before the call next week. Note I'm not available for the call
>> and I think Felix is away also.
>>
>> But we need to form a consensus quickly if we are to avoid delaying the
>> PR stage further.
>>
>> Regards,
>> Dave
>>
>>
>> On 17/07/2013 11:35, Yves Savourel wrote:
>>
>>> Hi Dave,
>>>
>>> In the case of QuEst, for the scenario I have in mind, one would for
>>> example perform the MT part with MS Hub, then pass that information to
>>> QuEst and get back a score that indicate a level of confidence for that
>>> translation candidate. So that's a step after Mt and
>>>
>> before any human looks at it.
>>
>>>
>>> I may be wrong, but "MT Confidence" seems to be a good place to put that
>>> information.
>>>
>>> Even if QuEst is a wrong example. Having MT Confidence restricted to
>>> *self-reported* value seems very limiting. But maybe I'm mis
>>> interpreting the initial aim of the data category.
>>>
>>> Cheers,
>>> -ys
>>>
>>> -----Original Message-----
>>> From: Dave Lewis [mailto:dave.lewis@cs.tcd.ie]
>>> Sent: Wednesday, July 17, 2013 12:25 PM
>>> To: public-multilingualweb-lt@w3.**org<public-multilingualweb-lt@w3.org>
>>> Subject: Re: MT Confidence definition
>>>
>>> Hi Yves,
>>> I don't necessarily agree with this based on the example you give in
>>> relation to quality estimation in Quest.
>>>
>>> Is not the goal of quality estimation to predict the quality of a
>>> translation of a given source string for a given MT engine training
>>> corpora and training regime _prior_ to actually performing the
>>>
>> translation?
>>
>>>
>>> In which case it would be an annotation of a translation but of a
>>> _source_ with reference to an existing or planned MT engine (which you
>>> rightly say in response to Sergey can be resolved via the
>>>
>> annotatorsRef).
>>
>>>
>>> So while the basic data structure of mtConfidence would work for, the
>>> use case, name and wording don't i think match the use of MT QE.
>>>
>>> Declan, Ankit could you comment - I'm not really an expert here, and not
>>> up to speed on the different applications of MT QE.
>>>
>>> cheers,
>>> Dave
>>>
>>>
>>> On 17/07/2013 08:29, Yves Savourel wrote:
>>>
>>>> Hi all,
>>>>
>>>> I've noticed a minor text issue in the specification:
>>>>
>>>> For the MT Confidence data category we say:
>>>>
>>>> "The MT Confidence data category is used to communicate the
>>>> self-reported confidence score from a machine translation engine of the
>>>> accuracy of a translation it has provided."
>>>>
>>>> This is very limiting.
>>>>
>>>> I think it should say:
>>>>
>>>> "The MT Confidence data category is used to communicate the
>>>> confidence score of the accuracy of a translation provided by a machine
>>>> translation."
>>>>
>>>> (and later: "the self-reported confidence score" should be "the
>>>> reported confidence score").
>>>>
>>>> There could be cases where the confidence score is provided by
>>>> another system than the one that provided the MT candidate. The QuEst
>>>> project is an example of this
>>>> http://staffwww.dcs.shef.ac.**uk/people/L.Specia/projects/**quest.html<http://staffwww.dcs.shef.ac.uk/people/L.Specia/projects/quest.html>
>>>> )
>>>>
>>>> Cheers,
>>>> -ys
>>>>
>>>>
>


-- 
*Dr. Declan Groves
Applied Research and Development Coordinator
Centre for Next Generation Localisation (CNGL)
Dublin City University

email: dgroves@computing.dcu.ie <dgroves@computing.dcu.ie>
 phone: +353 (0)1 700 6906*