The role of statistics in a selective theory of language acquisition (
more...)
While research in the acquisition of syntax has largely
focused on the necessity of abstract representations and the poverty
of the stimulus with respect to these representations, very little
research has asked how learners use the input to identify these
representations. At the same time, research showing that infants are
highly sensitive to the statistical structure of the input is often
silent about the nature of the acquired representations. I present
several experiments illustrating the role of statistical learning in a
selective theory of syntax acquisition. I show (a) that infants can
use statistical information to identify hierarchical phrase structure
in an artificial grammar, (b) that the acquired representations allow
for generalization to unobserved sentence structures, and (c) that
statistical generalizations to be found in the input have consequences
for morphosyntax that go beyond what can be inferred simply from the
distributions. Hence, to the extent that learners use statistical
information in learning syntax, they are doing so by comparing that
information against the predictions of precise alternative syntactic
representations.
3:30 p.m., Machmer W-23
3:30 p.m., Machmer W-23
Lexical Items in Complex Predication
3:30 p.m., Machmer W-23
Crosslinguistic Variation in Comparison Constructions (
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I will parallel sets of data on comparison
constructions from several languages. On the basis of
the cross-linguistic differences observed, we propose
three parameters of language variation. The first
parameter concerns the question of whether or not a
language's grammar has incorporated scales into
adjective meanings. The second parameter
differentiates between languages that allow
quantification over degrees in the syntax and those
that do not. Finally, we propose a syntactic parameter
that concerns options for syntactically filling the
degree argument position of a gradable predicate.
3:30 p.m., Machmer W-23
Friday, February 27, 2009
Raising Verbs As Quantifiers? (
more...)
The English sentence below is unambiguous: it has reading (i) but not (ii):
(1) In May only Mary began to get good roles.
(i) Mary is the only person (say, actress) whose situation changed in
such a way that before May she didn't get good roles, and after May
she was getting ones.
(ii) The overall situation changed in such a way that whoever might
have been getting good roles before May, after May only Mary was getting ones.
Reading (ii) is not even expressible in English in a straightforward
manner. But in Hungarian, Italian, Spanish, Russian, Finnish,
Shupamem, German, Dutch, etc. there is a straightforward way to
express (ii). For example:
(2) Ma'jusban elkezdett csak Mari kapni jo' szerepeket.
May-in prefix-began only Mary get-inf good roles-acc
[only reading (ii)]
(3) In mei begon alleen Marie goede rollen te krijgen.
in May began only Mary good roles to get
[ambiguous, but reading (ii) may be preferred]
It will be argued that, despite the superficial similarity,
Hungarian-type and Dutch-type languages pull different tricks. In
connection with the Dutch-type trick, one question is whether the
quantificational content of "begin" is represented explicitly in
syntax, or only in the semantics. The talk will present some initial
considerations in this connection.
3:30 p.m., Machmer W-23
Friday, February 20, 2009
Syntagmatic simplicity bias in human and artificial learners (
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(In collaboration with Joe Pater, UMass Amherst, and Michael Becker, Reed College)
Phonological dependencies in natural language tend to be assimilatory or dissimilatory, i.e., they relate two tokens of the same phonetic feature in an utterance. Six minimally-different experiments in phonotactic pattern learning by English speakers support the hypothesis that single-feature dependencies, even when they are not
phonetically grounded, are detected more readily than two-feature dependences, even when they are phonetically grounded.
The single-feature learning bias is shown to emerge in a constraint-inducing and -weighting phonotactic learner when ``Greek-letter'' variables are restricted to instances of the same feature. The result of this restriction is that single-feature dependencies are supported by multiple overlapping constraints, leading to faster learning in
Maximum Entropy and Gradual Learning Algorithm learners, whereas two-feature dependencies must be learned piecemeal. This treatment unifies the bias towards syntagmatically-simple patterns with that towards paradigmatically-simple ones, and points towards applications of constraint multiplicity and constraint generality in explaining learning and typology.
3:30 p.m., Machmer W-23