[Nettime-bold] Re: <nettime> The cultural bias of translating programs

["Julian Dibbell" <julian@mostly.com>]

Felix Stalder, commenting on Wade Tillett, wrote:

> >I wondered how much text degrades while it is put in a translator. Like
> >the experiment, I wrote this text in the babelfish and translated it the
> >French-English one and the English-French one until the text becomes '
> >produces ' the left side with us see...
>
<...>
> What was really interesting in Wade's experiment is to see that a text
> indeed does stabilize. Stabilization indicates that this version of the
> text contains only words that are, from the point of view of the
> translating program, unambiguous in both languages. And the way it
> stabilizes reveals the bias of the translating algorithm. In Wade's case,
> the translator seems reveals a bias towards business prose (probably
> that's where the market is for the high-end version).  It would be
> interesting to see if stabilization occurs in all translating programs at
> the same point, or if different translating programs have different types
> of biases.


See also my "After Babelfish" (at
http://www.feedmag.com/book2/essay_dibbell.html and also posted to nettime a
few weeks back). In that essay I did an experiment similar to Wade's, using
a Yeats poem and the Portuguese-English Babelfish. That program tends to
produce a slightly wackier text than those that translate French or German,
I find. Why? Because Portuguese is a "minor" language, with a smaller
market, and therefore has gotten less attention from the Babelfish
dictionary tweakers. And there's no getting around it: only many, many
person-hours of hand-tweaking a given language-pair can produce a halfway
decent machine translator. There is no magic algorithm for it. Consequently
these are very capital-intensive -- and therefore market-sensitive --
products. Which means that the English-French translator does a better job
than the English-Portuguese, and the Icelandic-Hindi will never see the
light of day.

So Felix is right in more ways than one. Markets do help build cultural bias
into machine translators -- not only by warping the vocabulary of a given
language pair toward a particular context (e.g., the business world), but by
warping the overall effectiveness of the pair as well.


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