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For what it's worth, I tried the translation demo[1] on some Wikipedia text in Italian and French, along with Google Translate on the same text, and Watson seem

by comex 10y ago

For what it's worth, I tried the translation demo[1] on some Wikipedia text in Italian and French, along with Google Translate on the same text, and Watson seemed nearly on par but consistently slightly worse. (I also tried Bing, which seemed more even with Google.) I guess this is to be expected, given the relative lack of importance to IBM, but I was vaguely hoping that Watson could somehow afford to spend more CPU time on it or something (after all, their main business is selling access; Google and Bing also do that but mainly exist as a free tool for consumers) and get a better result. Oh well.

Bartweiss 10y ago
I think this may boil down to dedicated intelligence. Google Translate is an entire project devoted solely to efficient, human-useful text translation, where Watson is a more general-purpose language processor. Certainly Watson must have dedicated translation logic, but I would be surprised if there are any narrow domains where Watson beats strong single-purpose competitors.
- pesenti 10y ago
  We do have a team dedicated to Machine Translation (the same team that actually introduced the statistical approach - the "IBM Models" - in the 90s) but that team had been focused more on non-European languages. If you search the literature you will find that the IBM team is leading for languages like Arabic and Chinese but trailing for European language. We are working on that.
  - Bartweiss 10y ago
    This is a really interesting response, thank you (and thanks for answering so many questions in this thread). That result makes a lot of sense - Google has been working with the huge corpus of English-European translations (e.g. UN reports) and getting impressive results largely because there's so much data available with such direct equivalences. Just based on personal experimentation, they're much less capable with longer "translation distances" like phonogram<-->logogram and Indo-European<-->Sino-Tibetan. I didn't know IBM was leading on those long-distance translations, that's cool to hear.

by comex 10y ago

Bartweiss 10y ago

I think this may boil down to dedicated intelligence. Google Translate is an entire project devoted solely to efficient, human-useful text translation, where Watson is a more general-purpose language processor. Certainly Watson must have dedicated translation logic, but I would be surprised if there are any narrow domains where Watson beats strong single-purpose competitors.

pesenti 10y ago
We do have a team dedicated to Machine Translation (the same team that actually introduced the statistical approach - the "IBM Models" - in the 90s) but that team had been focused more on non-European languages. If you search the literature you will find that the IBM team is leading for languages like Arabic and Chinese but trailing for European language. We are working on that.
- Bartweiss 10y ago
  This is a really interesting response, thank you (and thanks for answering so many questions in this thread). That result makes a lot of sense - Google has been working with the huge corpus of English-European translations (e.g. UN reports) and getting impressive results largely because there's so much data available with such direct equivalences. Just based on personal experimentation, they're much less capable with longer "translation distances" like phonogram<-->logogram and Indo-European<-->Sino-Tibetan. I didn't know IBM was leading on those long-distance translations, that's cool to hear.