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Military Communications and Information Technology: A Trusted ...

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Chapter 3: <strong>Information</strong> <strong>Technology</strong> for Interoperability <strong>and</strong> Decision...<br />

277<br />

We got a BLEU-Score [21] of 8.06 for Google’s output <strong>and</strong> a BLEU-Score of 9.69<br />

for the ISAF-MT translation. To our knowledge, there is no rule-based translation<br />

system for Dari <strong>and</strong> German publicly available. For further reports on evaluation<br />

results regarding the ISAF-MT (e.g., BLUE-Scores) system see [4].<br />

Figure 5. Excerpt of Translation Ouput generated by the ISAF-MT SMT System<br />

An approach for applying SMT to intelligence processing<br />

Translations produced by SMT can be of different quality, depending on<br />

the complexity of the input text, on the SMT system, the available training data,<br />

the language pair, etc. In any case, to bring across the meaning, translation does<br />

not have to be perfect. We therefore argue that the output of SMT systems, even<br />

though of varying quality, can support the intelligence process in different ways.<br />

This concept is presented in Figure 2, <strong>and</strong> will be discussed in the following.<br />

a) First impression / idea of text content for the human analyst: On the basis<br />

of a translation produced by SMT, even if not of perfect quality, the human analyst<br />

can infer the document’s content. Such a broad translation can serve<br />

the human analyst in a first screening of the documents to decide whether<br />

the document is of any relevance <strong>and</strong> should be passed on for proper (human)<br />

translation or a different further analysis. Apart from that, under the dogma<br />

“any translation is better than no translation” this rough translation can help<br />

the analyst with the different intelligence tasks, where texts in different languages<br />

need to be processed. This would apply if no translator is available, or,<br />

for efficiency reasons.<br />

b) Automatic collection: A rough translation can also serve as input for automatic<br />

information retrieval <strong>and</strong> for automatic classification. To automatically search<br />

for relevant documents in different languages, it is usually sufficient if the broad<br />

content of the documents is provided. The same applies to automatic classification<br />

of the relevance of documents according to the mission’s needs.

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