Tag: information quality

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Common Sense Advice about Machine Translation and Content

Translation Technology

You’d need to be living on the moon if you still don’t get it about how data quality impacts machine translation quality (actually, every kind of translation). But, what does this fact really mean when communicating with content creators?

Writers, and information developers generally, have to contend with all sorts of “guidance” about how they must create content to make it easily “translatable”. I am against that sort of positioning.

Content creators need and want guidance on how to make their content usable, not translatable. There is no conflict between making content readable in English and making it easily translatable, and vice-versa. There is a conflict between telling content creators to make their content translatable and not accounting for content style, source user experience, and especially the motivations and goals of the content creators themselves.

Well, I have been reading the Microsoft Manual of Style (4th Edition), recently published, and I am delighted to see there is a section called “Machine Translation Syntax”.

Microsoft Manual of Style 4th Edition. Sensible stuff about machine translation.

Microsoft Manual of Style 4th Edition. Sensible stuff about machine translation. Did I mention that I got a new bag from Acrolinx?

Here is what that section says:

“The style of the source language has significant impact on the quality of the translation and how well the translated content can be understood.”

The style of the source language. Brilliant appeal to the audience! What follows is a baloney-free set of 10 guidelines for content creators. Each guideline appears to be an eminently sensible content creation principle worth respecting, regardless of the type of translation technology being used, or even if the content is not explicitly destined for translation at the time of creation.

You can read the 10 guidelines on the Microsoft Press blog.

Well done Microsoft, again (no, I am not looking for a job). Let’s see more of this kind of thing from everyone!

I’ll do a review of my new Acrolinx bag when time allows.

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Ultan Ó Broin (@localization), is an independent UX consultant. With three decades of UX and L10n experience and outreach, he specializes in helping people ensure their global digital transformation makes sense culturally and also reflects how users behave locally.

Any views expressed are his own. Especially the ones you agree with.

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From Back End to Front End

Language in Business

I spoke recently at UA Europe 2010. Ostensibly, a conference about software user assistance, localization was, naturally, featured. It was so encouraging to see the Irish software industry represented in the shape of the Alchemy Software Development stand in the exhibition space, and everybody had great things to say about MadCap Software’s Lingo product.

Naturally, some of the speakers mentioned localization in their presentations too. I have to say, a lot of what I heard was not very positive. One of the more colorful speakers described the localization process as nasty, expensive, messy and generally one big pain (and coming from someone working in user assistance, that really is something). Another speaker said his company now preferred to hire internal translators rather than have LSPs coordinate their translation efforts across EMEA and APAC.

Generally, on hearing all this, I was reminded of the state of internally-driven innovation (sorry but I regard Google Translate and crowdsourcing as external) in the localization space and the lack of a pervasive thought leadership (there are some exceptions, naturally). When I spoke with conference delegates, it seemed a major part of the problem is the continued disengagement of localization, translation, whatever you like to call it – I prefer global information delivery – from the user experience. Localization (actually user assistance too) is too often couched in narrow “back-end” terms of content management systems, workflows, professional linguists, and invisible project management. Because that’s what it probably is, for many.

And then there are translation memories (TMs). I am surprised some of these things haven’t been added to the list of world heritage sites by the UNESCO World Heritage Centre given the sanctity they’ve been accorded. Anyone who has ever been told they cannot change or update source content because it will upset translation memory matching will relate to this back-end mentality (translation memories are, in fact, user experience liabilities in this regard).

Another thought leader, respected industry commentator Renato Beninatto, argues that TMs will be free or irrelevant within five years. Bring it on, I say. After bootstrapping a statistical machine translation engine you might as well give them away in my opinion, probably with a health warning given what we know about dirty data.

Generally, for both user assistance and translation I was left with the feeling that this “back-end” fundamentals approach needs to change to a “front-end” information quality perspective; one where the terminology and language of users (or their “conversation”, if you like) become the real information assets and decision-making arbiter. Source content creators become curators, facilitators, of user decisions about information creation and quality. Of course, this must all line up with business requirements if you’re out to make a profit, but I don’t see how the front-end approach conflicts with delivering quality information globally, increasing user engagement, market share, and the bottom line.

Generally, the way forward in my opinion to turn the back end into the front end and bring the consumers and creators of translated information (source or user generated) to center stage.

Let’s see some more thought leadership on this subject from the GILT industry and the localization conference scene opening up to people who bring fresh perspectives from outside the industry.

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Ultan Ó Broin (@localization), is an independent UX consultant. With three decades of UX and L10n experience and outreach, he specializes in helping people ensure their global digital transformation makes sense culturally and also reflects how users behave locally.

Any views expressed are his own. Especially the ones you agree with.

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Measuring Information Quality: What’s Missing?

Language in the News, Personalization and Design

A lot written about information quality recently. But how do we measure it?

There is a perception out there that information quality generally is very poor. But how do we know? All that digital content out there, but most of it is never read, and only a fraction of that is ever translated (and translators are often the only readers of that content). Just because a user guide isn’t read doesn’t mean the information itself within is poor quality. Perhaps, the accompanying software’s usability is spectacularly good and so it isn’t needed? Who knows?

In the GILT industry, information quality is all too often only assessed in terms of the cost, time, and effort to produce and then translate content (and usually one function is measured in isolation of the other). We have all kinds of metrics about “spend” published, time-to-market statistics analyzed, the opinions of professional linguists and terminologists debated, complicated mathematical formulae promulgated (trust me, if you reach that level you’ve clearly no real work to do), QA checklists written, certifications from standards bodies waved under our noses, and all the rest, in an attempt to define information quality. All good, though how efficient or applicable to the real world some of these things are is debatable.

However, often there’s a decider of information quality that is missing from these methodologies: the user of the information.

We need to move the key determinant of information quality to the user community: engaging users, and research, analyzing and understanding how users search for, retrieve, and use information to solve problems. For example, what search keywords and phrases do they use? Which pages do they read the most? Which parts of those pages are read and how? And so on.

The tools and opportunities for this are everywhere. Ever studied web server logs? Done any eye tracking studies (see image below) before and after an information quality project? Conducted comprehension studies on the outputs? Observed how real users consume information? Found out what terminology they actually use when helping each other, on support forums, and when they customize and extend software? Reviewed what keywords they use for searching or analyzed user comments?


So, let’s look at costs and translatability issues, post-editing metrics, number of flagged errors in QA, and so on, sure. But let’s connect it to the user experience too, regardless of language, and give the user the final say. Make users the arbiters of information quality.

Otherwise, we’re really just talking to ourselves.

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Ultan Ó Broin (@localization), is an independent UX consultant. With three decades of UX and L10n experience and outreach, he specializes in helping people ensure their global digital transformation makes sense culturally and also reflects how users behave locally.

Any views expressed are his own. Especially the ones you agree with.

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Information Quality, MT and UX

Translation Technology

I’ve been working on an acrolinx IQ deployment for my employer Oracle (yes, I do have a real job). For many who go down this route, the claim that such initiatives are only being done because it will mean the instant arrival of machine translation (MT) will seem familiar.

The ‘translation process’ imperative is the wrong way to drive such initiatives. Instead, what is critical here is understand the notion of managing information quality for the user, regardless of the translation process. Because the language used in content, or information if you like, is a user experience (UX) issue.

It’s clear that a quality input (or source) gives better returns for every kind of translation. In the case of any language technology, clean source data delivers the best returns; and is becoming even more important as more and more turn to statistical machine translation.

Furthermore, the points made by Mike Dillinger at the recent Aquatic/Bay Area Machine Translation User Group meeting need re-emphasizing: MT does not require special writing; people require special writing. The rules for writing English source text for human translators, machine translators, and users in general, are the same.

Developing quality information in the first place, and then managing it, is the way to go.

acrolinxIQ flagging errors

So, forget about “controlled authoring” (manual, automated, or whatever other method of implementing it) and indeed “writing for translation” classes as the “mandatory prerequisite” for improved translatability or machine translation. Think and practise information quality as an end user deliverable in itself that has significant translation automation (and other) externalities.

I’d love to hear other perspectives on this, too.

If you’re interested in this notion of the primacy of information quality per se in the translation space, then read Kirti Vashee’s The Importance of Information Quality & Standards.

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Ultan Ó Broin (@localization), is an independent UX consultant. With three decades of UX and L10n experience and outreach, he specializes in helping people ensure their global digital transformation makes sense culturally and also reflects how users behave locally.

Any views expressed are his own. Especially the ones you agree with.

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