Applying Automated Language Translation at a Global Enterprise Level

By Rychtyckyj, Nestor; Plesco, Craig | AI Magazine, Spring 2013 | Go to article overview

Applying Automated Language Translation at a Global Enterprise Level


Rychtyckyj, Nestor, Plesco, Craig, AI Magazine


We have been applying AI and machine-translation (MT) technology at Ford Motor Company since the late 1990s. Our initial goal was to utilize MT to translate vehicle build instructions from English to the native languages in the countries and regions where our assembly plants are located. The source text utilized a controlled language that we developed, called Standard Language, and we initially thought that applying MT technology would be a straightforward process. Controlled languages, such as Standard language, restrict the complexity and ambiguity of human languages by restricting syntax and terminology (Huijsen 1998). As such, they have been utilized in a number of different industrial applications (Godden 2000). However, there were many issues dealing with technical terminology, ungrammatical aspects of Standard Language, Ford-specific terminology, and the need to process uncontrolled text that needed to be addressed. We partnered with Systran Software Incorporated and with AppTek (now SAIC) to use their machine-translation technology and also incorporated natural language processing (NLP) algorithms within our artificial intelligence environment to analyze terminology and modify the source text to improve translation accuracy (Rychtyckyj 2007). The need to support manufacturing expansion in non-English speaking countries in Eastern Europe and Asia (such as in Russian and Chinese) led us to add additional language capability and to develop translation glossaries for all of the supported languages. The automated language translation for manufacturing work continues and will expand as Ford's global manufacturing footprint increases. However, the international growth within the company was not limited to manufacturing only and we found that there are many different groups within the company that need some type of machine-translation solution. Therefore, in 2010 we deployed an internal web-based machine-translation solution that sought to leverage our work in manufacturing and make automated translation a reality for the entire company. In the following sections we will describe the process of delivering a new technology across an entire company and lessons that we learned.

Machine translation has become ubiquitous in the last few years. Since the advent of the first MT systems in the 1960s the technology has been supported by a few specialized vendors and the cost to develop machine-translation systems was significant. This situation has changed dramatically in the last few years as the introduction of statistical machine translation has decreased the development time and subsequently large companies such as Google and Microsoft have become heavily involved in machine translation. The main result of this is that most users have had some experience with the technology and will likely have some type of preconceived bias (either positive or negative) when they are introduced to it as part of their daily work.

Unfortunately, many users still treat machine translation as a "black box" technology and expect to receive high-quality translations suitable for their specific purposes (conversational, business unit jargon, and so on) given any sort of input without having to do any other work. Other users have had bad experiences and do not believe that machine translation can work well in any instance. A large part of our work is to educate and manage these user expectations so that they can use the technology effectively. For example, a very common request that we have is to translate screen headings and labels into another language as part of a conversion process. These headings are usually one or two word phrases that often contain abbreviations and acronyms. This type of translation is difficult for machine (and human) translation because there is very little context available and these phrases may be ambiguous in many cases without a detailed knowledge of the application. In these cases, it is critical that the users be aware of these limitations and have human posteditors available. …

The rest of this article is only available to active members of Questia

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

Applying Automated Language Translation at a Global Enterprise Level
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    Buy instant access to save your work.

    Already a member? Log in now.

    Author Advanced search

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.