DARPA Starts Ultimate Language Translation Project

An anonymous reader writes "Defense Advanced Research Projects Agency (DARPA) has launched the ultimate speech translation engine project that would be capable of real-time interpretation of television and radio programs as well as printed or online textual information in order to be summarized, abstracted, and presented to human analysts emphasizing points of particular interest." If combined with the tower of babel project we discussed earlier, it could only lead to awesomeness.

Comments

Too much too soon, or tackling wrong problem?

[Salvance]

This project, along with CMU's Tower of Babel, certainly get props in the coolness category, but the practicality is still lacking. I believe DARPA is barking up the wrong tree for now, or at least biting off more than they can chew.

Speech Recognition is the hardest problem to tackle on the path to recognition, and MUST be addressed before there is a viable real-time (or even delayed) translation engine. Currently, even the best speech recognition software can achieve at best ~80% accuracy when faced with a large vocabulary with no limits on speakers/dialects, and this level of accuracy is typically not achieved in real-time. While this 80% level is actually pretty good when transcribing to text (since the reader can typically decipher what the computer meant), it's downright awful if trying to translate the resulting text to another language.

For example, if I say "I like ice cream" into voice recognition software and 'hears' "I like, I scream", the reader might understand what this means, particularly if they say it in context and aloud. However, let's say we translate each sentence into Spanish ("Tengo gusto del helado" and "Tengo gusto, yo grito" respectively, according to Babel Fish), and the speaker would be completely lost as the out of context phrases don't sound anything alike. In a natural language translation, even under relatively accurate recognition scenarios, would be frought with misunderstandings.

Once speech recognition is tackled, it's just a matter of translation then voice synthesis. Fortunately these problems aren't nearly as difficult, and current solutions would suffice (with the only pitfall being poor grammer in the destination language, and a robotic sounding voice).