5 ms·
The Systran system is quite old, check out how Hofstadter thrashed it some years ago in his "Le Ton beau de Marot"(http://en.wikipedia.org/wiki/Le_Ton_beau_de_M
by Jun8 17y ago
The Systran system is quite old, check out how Hofstadter thrashed it some years ago in his "Le Ton beau de Marot"(http://en.wikipedia.org/wiki/Le_Ton_beau_de_Marot http://en.wikipedia.org/wiki/Le_Ton_beau_de_Marot) (awesome book on machine translation and literature in general, BTW). Looking at these I thought that (i) Google totally blows the competition out of the water in French, Spanish, and German (I even found the German translation slightly more readable than the human one - "uneasy dreams" sounds better than the human's "anxious dreams"); but (ii) the Russian and Arabic translations are not very readable. Too bad they didn't provide a comparison in Chinese.
Many old school linguists often scorn the no-model, statistical approach to machine translation that Google adopts (my advisor was one of these), opting for more semantically-based models instead. I have yet to see results comparable to Google's (i.e. in unconstrained domains) from this school.
- sundarurfriend 17y agoHow can we know about the linguistic models that Google uses? Are these from some papers published by Googlers?
- Jun8 17y agoFor a simple introduction to their approach you can read Peter Norvig's explanation of how Google performs spell checking (http://norvig.com/spell-correct.html http://norvig.com/spell-correct.html) or his video lecture (http://www.catonmat.net/blog/theorizing-from-data-by-peter-norvig-video-lecture/ http://www.catonmat.net/blog/theorizing-from-data-by-peter-n...). You can get links to their results for NIST 2005 evaluation from here: http://googleresearch.blogspot.com/2006/04/statistical-machine-translation-live.html http://googleresearch.blogspot.com/2006/04/statistical-machi...