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"Buenos dias", "buenas noches" -- this was the first words in a foreign language I heard in my life, as a three-year old boy growing up in developing post-war Western Germany, where the first gastarbeiters had arrived from Spain. Fascinated by the strange sounds, I tried to get to know some more languages, the only opportunity being TV courses of English and French -- there was no foreign language education for pre-teen school children in Germany yet in those days. Read more



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Discussion Details




Title: Re: A Challenge to the Minimalist Community
Submitter: Peter Svenonius
Description: As a theoretical linguist, I remain unconvinced from the discussion so
far that building a parser of the kind proposed by Sproat & Lappin
(LINGUIST 16-1156) would be as important as they suggest. The
proposal, if I understand it correctly, is to get a computer to match a
corpus of e.g. newspaper texts to a set of ''hand-constructed'' trees
for the sentences in that text.

The allowable training procedure consists in feeding the machine
pairs of sentences and trees, I gather. Unless the trees more
information than is usual, it is not clear that this procedure resembles
what a child does when learning a language. Recent acquisitional
work stresses the importance of child-directed speech in the
acquisition process, and the importance of supporting context. An
important clue to the difference between ''wipe'' and ''clean'' (to take a
well-studied example) is the contexts in which they're used. The
meaning difference, inferrable from the contexts of use, has subtle
syntactic effects that might or might not turn up in strings in a given
corpus. But such contextual evidence, abundant to the learner, is
necessarily ignored in the proposed scenario, because the trees
don't indicate what kind of thematic relation an object has to the event
it participates in. Certain aspects of intonation also turn out to be
extremely important in the acquisition process, but intonation is barely
indicated at all in written texts, and is underdetermined in standard
trees.

So the proposal seems to be to build a machine that works like
another machine (i.e. the kind that Sproat & Lappin have in mind), not
to build a machine that works like a human. There is a good chance
that such an exercise would simply fail to advance our understanding
of the human language faculty, the way the program Eliza fails to
advance our understanding of human intelligence.

I suppose that to make a human-like learning machine, I would first
want to build a corpus that resembled the actual input to which a child
typically attends, with intonation and supporting context. The input
would include such information as whether a discourse referent was
the same as one previously referred to or not, and whether a
discourse referent appeared to be proactive or simply passive in its
participation in a given event. These might be important clues for a
child deciding whether something is a definite article or whether
something is the syntactic subject (and these two matters might be
interrelated).

Then I would use that corpus as the training ground for testing my
simulacrum, because P&P (Principles and Parameters) theory is not
trying to describe a Language Acquisition Device that can learn a
language from the Wall Street Journal (with or without labeled
brackets), but a Language Acquisition Device that can learn a
language from a learning environment like the one described in the
preceding paragraph.

If my concerns are well-founded, then building a parser of the kind
described by Sproat & Lappin would not even be a milestone on the
road to a workable model of language; it would be a detour.

Peter Svenonius
CASTL (Center for Advanced Study in Theoretical Linguistics)
University of Tromsoe, Norway
Date Posted: 10-May-2005
Linguistic Field(s): Syntax
Language Acquisition
LL Issue: 16.1491
Posted: 10-May-2005

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