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<title><string language="fre"><![CDATA[Conférence invitée de Mark Liberman - From Human Language Technology to Human Language Science]]></string></title>
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<string language="fre"><![CDATA[JEP-TALN-RECITAL 2016 - Jeudi 7 juillet 2016
Conférence invitée
From Human Language Technology to Human Language Science
Mark Liberman
Résumé : Thirty years ago, in order to get past roadblocks in Machine
Translation and Automatic Speech Recognition, DARPA invented a new way
to organize and manage technological R&D: a ``common task'' is
defined by a formal quantitative evaluation metric and a body of
shared training data, and researchers join an open competition to
compare approaches. Over the past three decades, this method has
produced steadily improving technologies, with many practical
applications now possible. And Moore's law has created a sort of
digital shadow universe, which increasingly mirrors the real world in
flows and stores of bits, while the same improvements in digital
hardware and software make it increasingly easy to pull content out of
the these rivers and oceans of information.
It's natural to be
excited about these technologies, where we can see an open road to
rapid improvements beyond the current state of the art, and an
explosion of near-term commercial applications. But there are some
important opportunities in a less obvious direction. Several areas of
scientific and humanistic research are being revolutionized by the
application of Human Language Technology. At a minimum, orders of
magnitude more data can be addressed with orders of magnitude less
effort -- but this change also transforms old theoretical questions,
and poses new ones. And eventually, new modes of research organization
and funding are likely to emerge.]]></string></description>
<keyword><string language="fre"><![CDATA[Natural Language Processing]]></string></keyword><keyword><string language="fre"><![CDATA[Human Language Technology]]></string></keyword>
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<date><dateTime>2016-07-07</dateTime></date>
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