eBay has started working on a new approach to machine translation (MT) that could represent a breakthrough in machine translation quality. A team lead by artificial intelligence guru Hassan Sawaf, renowned for his work on hybrid machine translation systems, which combine different translation engines for better translation results. Sawaf calls what he’s trying to do for eBay “context translation,” since the new MT intelligence looks at a lot more than just a sentence when composing a translation. Russian is now complete and has provided a template for roll-out of additional languages that eBay hopes will create a multilingual market for eBay sellers regardless of their preferred language.
Leena Rao at TechCrunch describes the challenges eBay faces in emerging markets like Russia. “eBay is trying to curate inventory from a global base of sellers and surface this to buyers in emerging eBay markets based on what ships to them in their respective countries. A Russian user can go to the localized version of eBay and see all products that are listed in Russian. When they are inputting search terms in Russian, this engine will produce search results of listings that match the query in Russian. But the Russian user’s query will not be able to see posts that match their query that were written by sellers listing in English. In order to access English listings, which do represent a considerable number of the listings on eBay’s platform, Sawaf explains, the Russian user would have to input the query on eBay in English.
“Machine translation normalizes this,” says Sawaf.
With over 100 million products listed at any one time on eBay, pricing changes by the second, and lots of old stuff sold by amateurs and shipped around the world, there is a lot of back-and-forth between buyer and seller, which creates a lot of room for misunderstanding and missed opportunities. eBay thinks they can do better with their own in-house context translation solution.
This because the big database-driven statistical engines draw across the entire internet for their translation matches. Sure, using the sum of all human knowledge, (which is what language is, if you think about it), seems like a great way to find the perfect phrase in translation, but it’s not. This because the same phrase can mean different things in different contexts or domains, as they are usually called in the business. (I have to confess that I am not certain if Sawaf’s “context” is about domains or something else.) I always use the lame example of “The server is down” when I talk to my clients about this. Depending on context, that could mean that a computer has failed, or that a waiter has taken a spill. (I’m looking for a better example, if you got one, please post it.) The eBay user experience provides a unique domain, or really many domains depending on product category.
With all those millions of transactions, eBay has an enormous amount of data specific to that user experience, which can be used by the machine translation AI to provide more accurate translations specific to the language of eBayers, no matter what their native language.
Spanish and Portuguese are next. eBay press release here. Readers, if you want more on this, comment below, and I will reach out to Sawaf.