NIST data set |
BLEU-4 |
Site ID |
Language |
Overall |
Newswire |
Newsgroup |
Broadcast News |
google |
Arabic |
0.4569 |
0.5060 |
0.3727 |
0.4076 |
google |
Chinese |
0.3615 |
0.3725 |
0.2926 |
0.3859 |
GALE data set |
BLEU-4 |
Site ID |
Language |
Overall |
Newswire |
Newsgroup |
Broadcast News |
Broadcast Conversation |
google |
Arabic |
0.2024 |
0.2820 |
0.1359 |
0.1932 |
0.1925 |
google |
Chinese |
0.1576 |
0.2086 |
0.1454 |
0.1532 |
0.1300 |
Summary score table from NIST "Unlimited Plus Data" track
I included something about machine translation in the (pre- web log) Fortnightly Mailing Number 54. This June 2005 article by Gregory Lamb in the Christian Science Monitor is jargon-free, and explains the difference between the two main approaches to machine translation: rules-based - as developed by Systrans, and still used by Google; or statistically-based, as being developed by Google. (4/12/2006 - see also Not Lost in Translation, from the MIT Techology Review, by Stephen Ornes.)
As to the effectiveness of statistically-based methods, Google's system continues to score considerably better overall than the competition (who may or may not be using statistically-based methods), in both Arabic to English and Chinese to English, with the margin rather bigger for Arabic to English than for Chinese to English, in the US Government's NIST Translation Evaluations of machine translations of different genres of text (Newswire, Newsgroup, Broadcast News, Broadcast Conversation). Bear in mind however that a score of 0.503 out of a maximum of 1 (the best score achieved by Google for the translation from Arabic to English of Newswire genre, with scores for Chinese to English consistently worse) does not mean that the absolute quality of the translation was particularly high.
It is also worth noting, although the test regime was different, so this observation needs taking with a pinch of salt, that Google's results do not seem to have improved much on what was achieved in the equivalent 2005 NIST tests. (Here, for reference are the 2008 NIST results, which I have not had time to analyse.)
Updated 4/12/2006 and 1/1/2009
Crawling into the skin of a user....
A few weeks there was "climbing inside your users' heads and seeing your web site through their eyes". In Beyond Search, a 22/11/2006 article in Information World Review, by David Tebbutt, we have the equally extreme “a good information professional should be able to crawl into the skin of the user and understand their thought processes", in this case a quote from Susan Feldman, from the market intelligence firm IDC, in support of the argument that . The focus of Tebbutt's article is the shake-up that is happening in the commercial search world, stemming from the way in which vast tracts of content are now being routinely indexed, with storage costs no longer really relevant, and the increasing sophistication of the software systems that determine how search terms are turned into search results.
Where does this leave the information professional? According to Tebbutt:
On a related issue, and straying into territory that I observe rather than in which I have professional expertise, here is an interesting report of a discussion between Tim Berners-Lee ("father" of the Web) and Peter Norvig (Director of Research at Google) at the July 2006 American Association for Artificial Intelligence conference. This highlights the "divide" between people who want information and the links between it to be curated, with thought given to how both are described, and people who think that as more and more of the content "out there" is produced by amateurs, never going near an information or ICT professional, the only way forward is for search tools to extract meaning from the content without reliance on how that content has been categorised.
Posted on 01/12/2006 in News and comment | Permalink | Comments (0)
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