Language Weaver CTO Says Improvements to Statistical Machine Translation Expand Opportunities for Government Customers
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Language Weaver Co-Founder and Chief Technology Officer Daniel Marcu says that rapid advancements in the field of software-based statistical translation are providing government customers with a range of new, more powerful translation solutions.
Daniel is a recognized leader in natural language processing.
In the following podcast interview, Daniel says that both the speed and accuracy of statistical translation systems have improved exponentially in the past 10 years. He also explains how Language Weaver is working to further improve the applicability of its proprietary translation technology:
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July 9th, 2008 at 1:24 pm
Nice job Daniel and Tim. It would be interesting to hear a bit more about how governments use machine translation.
I wonder if it is enough to “pipe in” a feed from a monitoring station in a hot spot or do you have to “tune” the engine to teach it code word and references that might seem harmless.
For example, in the Jose Padilla case the prosecution explained the absence of any terrorism discussion in recorded conversations by claiming that the defendants were speaking in code. Thus “soccer equipment”supposedly meant guns, “eating cheese” meant violent jihad, etc.
How does machine translation keep up with the changing code?
July 11th, 2008 at 9:44 am
Hello! Please forgive me if this post is inappropriate, but I couldn’t find a direct email address on your blog. I’m Anton and I’m launching my new blog dealing with language translation issues and would appreciate the opportunity to discuss mutual collaboration. Thanks!