Military Communications and Information Technology: A Trusted ...

276 Military Communications and Information Technology...
Our project proved the usefulness of SMT for military purposes in terms
of fast system production and applicability of translation results. We showed that,
after building up the SMT infrastructure (computer cluster, procedures for building
corpora, etc.), a translation system for rough translation can be produced
rapidly [4]. We also argue that the system outputs translations that can support
military operations. This means that the translations generated by our SMT system
are of a quality that is good enough to capture the meaning of the input text, i.e. are
rough translations. This already applies to a system trained on only a few thousand
lines, for example, on the 4000 lines of high quality translations of our training
corpus. System performance improved with size of corpus data. Apart from that,
the integration of dictionaries significantly improved translation quality especially
when the system was trained on small data.
In our project we showed that SMT systems that can support military intelligence
can be produced rapidly. In order to build a translation system, training
data can be obtained from the internet. In case of insufficient amount of data
resources, as it is often the case for rarely spoken languages, the training corpus
can be produced by human translators. Additionally, available linguistic resources
can be usefully integrated, and, on the basis of linguistic expertise, system components
can be modified to adapt to the specific language pair. Such a system could
already support military intelligence. After more corpus development, as translation
quality increases with corpus size, the system could be applied for tasks of higher
complexity or difficulty. For a more detailed description on the fast production
of SMT systems in the context of military missions, see [4].
The ISAF-MT SMT system outputs translations of different quality, i.e.,
translation quality can vary from very bad to very good translations. In Figure 5
you can see an example translation of a newspaper article generated by a current
version of our ISAF-MT system. Bad translations can be caused by words or
phrases that have not been translated from Dari to German. Furthermore, words or
phrases can occur that have been translated into wrong German words or phrases.
Translations that are useful for military purposes can be sentences that are not
good in terms of naturalness or correctness of the target language but that bring
across the semantic content of the source sentences. There are also translations that
capture the right semantic content of the Dari sentences and that are correct and
natural German sentences. Overall, we argue that a translated document consisting
of translations of different quality (like in Figure 5) can bring across the meaning
of the source document. Thus, even a translation system that has been trained on
only a small number of sentences, like our system, can be useful in the context
of military intelligence.
Though machine translation is an active research area, to our knowledge, there
are not many systems for translating Dari to/from German. We have compared our
SMT system to Google Translate [20]. We ran Google’s Persian to German translation
on a random test set that has been extracted from our Dari-German Corpus.