Dispelling 3 Common Myths about Machine Translation

January 21, 2013

In the first installment of our Machine Translation series, "Introduction to Machine Translation," we provided a brief history of MT, presented an overview of the technology and touched on its use in business today.

Machine Translation has endured a questionable reputation over the years, and it is understandable. For a profession/craft (translation) that touts accuracy and cultural appropriateness as the two main indicators of quality for final output, relying on a tool that only gets you a percentage of the way there, a percentage of the time seems the antithesis to what you are trying to accomplish.

However, each year it seems MT is improving - when in the right hands and applied to the right content with the right process.

In our second installment of the MT series, we will discuss three myths of MT in effort to dispel some common misconceptions and help provide further clarification of its applicability.

Myth #1: "Machine Translation will be useful in the future, but we're not there yet."

No need to climb into your DeLorean and fire up the flux capacitor - the future is here today! But the "current" future with Machine Translation is not quite as advanced as science fiction movies would have us hope.

Today we do see an impressive sample list of well-known corporations and organizations currently investigating and/or using MT technology in some form. Companies include:


  • Adobe
  • Autodesk
  • Caterpillar
  • Cisco
  • Citrix
  • Dell
  • eBay
  • Google
  • Harley Davidson
  • Hewlett-Packard
  • Intel
  • John Deere
  • Medtronic
  • Microsoft
  • Oracle
  • Philips
  • Siemens
  • Yahoo!

[see the TAUS Member Directory]

What is impressive is that many of these companies and other organizations report that using MT has helped them to cut turnaround times and costs for MT-related projects. Please keep in mind that none of these companies use MT exclusively and some do employ post-editing effort to reach a final product.

Are these companies using MT for the home page of their websites or for the advertisements you see on the subway? Most likely not, but you would find it surprising to hear how companies are applying MT and the feedback they have about it, which leads us to Myth #2…

Myth #2: "Machine Translation quality is so bad, that any translations done by machine are useless."

We have all heard appalling translations that may have been done by machines. And we all know it's a bad idea to use Google Translate to do your French homework. However, it would be unfair or misguided to say that Machine Translation quality is so bad that it cannot possibly have any practical use. Let's look at some real-world examples that should help lay this myth to rest.

Catherine Dove, Quality Lead at PayPal Inc. . probably raised more than a few eyebrows at the 2011 TAUS User Conference when she said, "Human quality is not good enough for PayPal." (See video from the conference at the TAUS YouTube Channel). PayPal faces a number of challenges when localizing their content into 24 languages. For example, their content does not consist of complete sentences and contains a lot of tags. It is challenging for human translators to handle the tags correctly and they often make mistakes. On top of that, PayPal translators must work within very tight deadline constraints, but applying multiple linguists to the same project leads to inconsistencies. PayPal is getting help from MT, using a process they call "Machine Aided Human Translation." Catherine Dove explained that, for their content, MT is better at Human Translation at handling tags and the "MAHT" process helps PayPal improve consistency, allows human post editors to focus on style, fluency, voice, brand & tone, and drives internal rework of translation content down by 20%.

At the 2012 TAUS User Conference, a panel of MT users from companies like Microsoft, eBay, Cisco and Dell was asked how they get MT non-believers at their respective organizations to buy into the process and believe that MT quality can be good enough. Their answers were very insightful. (See video from the conference at the TAUS YouTube Channel). Tim Young, Sr. Operations Manager at Cisco, explained that Cisco feels confident enough in the quality of their MT output due to the post-editing process and relationships with their post-editing service providers, that those conversations around quality are giving way to more meaningful conversations about things like time-to-market and the authoring & content management process.

Wayne Bourland, Director of Translation at Dell likened the application of MT in their process to the application of Translation Memory technology; each tool is just a piece of the localization puzzle and the human touch is still there in the form of post-editors. He also brought up an interesting point that we will explore in later blogs: the idea that end-users may not expect "perfect" translation quality and that "good enough" quality can satisfy the language needs of end-users while allowing Dell to focus on delivering the other things their customers need, such as fewer clicks on Dell.com to get to the content they seek.

When you hear it from the lips of companies like these, it is impossible to deny that MT is useful & applicable today and the quality can be acceptable (or above par) in certain scenarios.

Myth #3: "Machine Translation will replace human translators."

Never say "never", but it is highly unlikely Machine Translation will replace human translators in our lifetime. Machine Translation is not a disruptive innovation; human translators will not suffer the same fate as film cameras, cassette tapes and floppy disks!  There will always be a call for human translators as long as machines are not able to pick up on context, idioms, slang, style, tone or cultural nuance as effectively as the human brain. In fact, who better to run MT systems, than qualified translators?

Let's take a closer look at "context" - content that proceeds and follows a segment, which influences the meaning of that segment. The word "lie" for example can have many different meanings depending upon the context in which it is used. Recall that a Statistical MT engine works on the basis of probabilities: for each segment of source text, there are a number of possible target segments with a varying degree of probability of being the correct translation. The software will select the segment with the highest statistical probability, independent of contextual information found in nearby segments. Most Statistical MT engines cannot pick up on contextual details.

It appears that translators have nothing to fear, however, most of the pushback against MT seems to come from the professional human translator crowd. Self-preservation is a strong instinct and surely a sizable percentage of the world's 700,000+ translators feel threatened by this technology. Some may even do their best to discourage its use by proliferating some of these myths we have discussed.

Machine Translation and Human Translation are not mutually exclusive; as we have seen, companies like PayPal, Dell and Cisco use MT as only a step in their localization processes. Perhaps one day more translators will be willing and able to use MT as a tool in their work, just as they use Translation Memory now after years of reluctance.


By now, it should be clear that Machine Translation (1) is in use today and (2) is part of the process that provides corporate users with good or "good enough" quality, a process which also includes (3) human translators, who are and will always be an essential piece of the localization puzzle.

Hopefully this helps to dispel some of the common myths around Machine Translation. Can you think of any other common Machine Translation myths or misconceptions? If so, we invite you to leave a comment!

You may also find some of the following articles and links useful:

Additional resources on language translation services

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  • minuettaOn Jan 22, minuetta said:
    Myth #4 perhaps should be "MT is cheaper" - I have seen a lot of stats on this, but when you really analyze the cost of MT / setting up MT + Human post-editing..there is almost no saving. I would be happy to receive comments or links that prove the contrary :)
  • GPIOn Jan 22, GPI said:
    Excellent suggestion, Minuetta! How could I have forgotten cost? Developing or buying a Machine Translation solution can be very expensive up front, depending on which route organizations take. It usually requires a lot of resources to train an engine and refine the process to the point where it generates good quality translations (and then many organizations pay for post-editing on top of that). I haven't seen a lot of data published publicly about return on investment for Machine Translation initiatives, but I would venture to guess that the users who claim they are saving 20-50% on translation costs (with acceptable quality results) have invested a significant amount of time and resources to get to that point. But, the Adobes and Dells and Caterpillars of the world have enough content to put through their engines that they probably pass the break-even point and realize true cost savings sooner rather than later.

    I'll see if I can find any data/resources that indicate what kind of ROI companies are getting on MT and will be sure to post about it in future blogs. Thanks for reading!
  • Udi HershkovichOn Jan 22, Udi Hershkovich said:

    Excellent overview!
    I really enjoyed reading it. Keeps things simple and to the point.

    I can't help but note that both examples you have brought forth (PayPal and Dell) just happen to be using Safaba's Enterprise Machine Translation (www.safaba.com/machine-translation/enterprise-machine-translation). Companies see great value in MT and it is up to those early adopters and industry leaders to show others the way.

    Looking forward to reading your upcoming posts ;)

    Best Regards,
  • Machine Translation (MT) – Do You Buy These 3 Common Myths  - Medialocate USA Inc.On Jan 23, Machine Translation (MT) – Do You Buy These 3 Common Myths - Medialocate USA Inc. said:
    re, but we’re not there yet.” Not necessarily true. What is impressive is that many companies and other organizations (see list in complete article here) report that using MT has helped them cut turnaround times and costs for MT-related projects …
  • Translation industry at the crossroads | AnglicityOn Jan 24, Translation industry at the crossroads | Anglicity said:
    ranslation-computer-getting-closer-conquering-babel Lauren Nemec , Dispelling 3 Common Myths About Machine Translation, http://blog.globalizationpartners.com/machine-translation-mt.aspx, 21 January 2013 Anthony Pym et al, The status of the translation …
  • Dispelling 3 Common Myths about Machine Translation | Best of the WebOn Jan 29, Dispelling 3 Common Myths about Machine Translation | Best of the Web said:
    mpanies using MT for the home page of their websites or for the advertisements you see on the subway? See full story on globalizationpartners.com Comments Comments are disabled for this post. try{ clicky.init(66557793); }catch(e){}
  • Véronique PascalOn Feb 06, Véronique Pascal said:
    I'm an experienced translator and I'm ok now to consider MT post-editing jobs as review and proofreading jobs, which I do since years. One of my customers offers to pay 75% of my full rate for MT post-editing of Microsoft documents. What do you think about this rate? Is it fair?
  • GPIOn Feb 08, GPI said:
    Salut, Veronique, et merci à lire! I'll continue in English, because my French is very rusty. I am not really in a position to comment on rates, but I have heard that agencies usually charge their clients between 40-60% of the usual rate for post-editing of machine translated content, so your rate seems to be in line with (or higher than) that average. My recommendation is to make sure your customer provides you with very clear post-editing guidelines, otherwise you could spend too much time and effort on the work. Best of luck with your post-editing endeavors!
  • SebastiánOn Apr 06, Sebastián said:
    These days, many companies rely on MT, that's why their websites in other languages are never understood by the public!
  • Udi HershkovichOn Apr 06, Udi Hershkovich said:
    You would not be advised to use raw Mt output for publication-grade material like a website. It has its place but not in business-critical collateral. You still can and should use MT for these types of content but have them reviewed and post edited at least by bi-lingual speakers if not by professional linguists before you publish.
  • Brace Yourself, Crowd-Translation is Already Here | Adventures in Freelance TranslationOn Nov 13, Brace Yourself, Crowd-Translation is Already Here | Adventures in Freelance Translation said:
    terms of simultaneous translations by using crowd-sourced data. Blogger Federico Pascual has also written to dispel the age-old myths on the quality or performance of machine translations. His conclusion? By now, it should be clear that Machine …
  • Brace Yourself, Crowd-Translation is Already HereOn Nov 29, Brace Yourself, Crowd-Translation is Already Here said:
    terms of simultaneous translations by using crowd-sourced data. Blogger Federico Pascual has also written to dispel the age-old myths on the quality or performance of machine translations. His conclusion? By now, it should be clear that Machine …
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Federico has over 10 years' experience as a globalization engineer managing a wide range of software and website globalization projects (internationalization I18n + localization L10n). His expertise spans software and website internationalization and localization processes, standards and tools as well as locale specific SEO. Federico has completed hundreds of successful globalization engagements serving as lead I18n architect involving different programming languages. He is a certified developer in several content management systems and helps clients create world-ready applications, utilizing development practices that are faster, more economical, and more localization-friendly.

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