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<p><font size="4"><br></font><br><div class="gmail_quote"><div><div><div><font face="Calibri"><span></span><span>Dans le cadre des séminaires du Labex-EFL 2013, veuillez noter que les prochaines sessions seront assurées, en janvier 2013, par les deux professeurs invités suivants:</span><br>
<u><br></u></font></div><div><font face="Calibri"><u><br></u></font></div><div><div><div><div><div><div><ul><li><span><b><font face="Calibri" size="5"><u>Janet Fodor</u></font></b></span></li>
</ul><div><font face="Calibri"><span><b>Distinguished Professor, Graduate Center, City University of New York</b></span></font></div></div></div><div><font color="#3b3b3b" face="Calibri"><span><b><br>
</b></span></font></div><div><font face="Calibri"><b>07/01/13, 14h-16h</b><br><b>Lieu: Université Paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div><div><font face="Calibri"><br></font></div></div></div></div>
<font face="Calibri"><u><span style="text-align:center;">Modeling Language Acquisition: From Math to Biology (</span><span style="text-align:center;">Joint work with William Sakas)</span></u></font></div><div><span style="font-family:Calibri;">The modern study of language learnability was founded in the 1960’s following Chomsky and Miller’s remarkable collection of papers on the formal properties of natural language, including mathematical modeling of the relations between properties of languages and properties of the grammars that generate them. The learnability studies that ensued, including the groundbreaking work by Gold (1967), were mathematical also, and hence untrammeled by any demands of psychological plausibility. For instance, under a psychological interpretation of Gold’s learning algorithm the grammar hypothesized by a learner in response to linguistic input might bear no relation to the properties of that input. By contrast, we expect that when children change their grammar hypotheses in response to a novel input sentence, the properties of that sentence guide them toward a new grammar which could incorporate it. It would be odd indeed (cause for concern!) if a child shifted from one grammar to an arbitrarily different one, just because the former proved inadequate.</span></div>
<div><font face="Calibri">For learnability theory to become a contributing partner in the modeling of real-life language learning, it therefore had to incorporate more realistic assumptions about languages and language learners. The first noteworthy study in this tradition was by Wexler & Culicover (1980). Their aim was to show that it was possible for a linguistically authentic grammar to be acquired by computational operations of a reasonably modest complexity, on the basis of a language sample consonant with the language that toddlers are exposed to. In other words, a learning model for natural language was to be developed which was computationally sound, but also psychologically feasible and in tune with current linguistic theory.<br>
No sooner had W&C completed their learnability proof than the linguistic theory that it presupposed (Chomsky’s Extended Standard Theory) was abandoned. In 1981Chomsky introduced his new Government-Binding (GB) theory, which had universal principles, and a finite collection of parameters as the means to codify cross-language syntactic differences. Chomsky was not explicit about the mechanism for setting the parameters, but he evidently regarded it as more or less automatic, instantaneous and computation-free, offering an explanation for how children acquire a rich target language in just a few years. Nevertheless, a decade passed before any parameter-setting model was computationally implemented. Moreover, the models then developed all departed from Chomsky’s original conception of triggering, by portraying learning as a process of testing out whole grammars until one is found that fits the facts of the target language. Instead of n isolated observations needed to trigger n individual parameters, these approaches require the learner to search through the vast domain of 2<sup>n</sup> grammars.<br>
In our work we have tried to hold tight to the notion of input guidance embodied in Chomsky’s original concept. We maintain that an input sentence not yet licensed by the learner’s grammar can <u>reveal</u> to the learning mechanism, without resort to extensive testing or trial-and-error, which parameter settings could license it. In the ‘Structural Triggers’ framework that we have developed, parameter values are taken to be UG-specified I-language entities in the form of ‘treelets’ (sub-structures of sentential trees), e.g., a PP node immediately dominating a preposition and a nominal trace, which would establish the positive value of the preposition-stranding parameter. Because treelets are structured entities, they aren’t directly observable in a learner’s primary linguistic data. Also, they may contain phonologically empty categories, such as the trace in the stranded-preposition treelet. What is observable by a learner is only the ‘E-trigger’ for that parameter value, e.g., a sentence with a preposition lacking an overt object. On hearing such a sentence, the learner must somehow recognize it as a manifestation of the abstractly specified I-trigger. In a structural triggers learning model (STL), this is achieved by the learner’s sentence processing mechanism (‘the parser’), assumed to be innate. The parser processes sentences in the usual fashion, applying the learner’s currently best grammar hypothesis, and upgrading it on-line if and where it finds that a new treelet is needed in order to parse an incoming sentence. In this respect, and only this, a child’s processing of sentences differs from an adult’s. This process of patching gaps in parse trees makes maximum use of the information that the input contains, and with the least wasted effort since presumably a child’s primary goal on hearing a sentence is to parse and understand it, as part of normal social interaction (What is Mommy saying to me?). Importantly, the parsing mechanism is what provides the link – notably missing in the original switch-setting metaphor – between the E-language facts available to the child and the I-language knowledge that is acquired. This concept of grammar acquisition as continuous with sentence processing fits well with the recent shift of emphasis to a conception of the language faculty as a biological organ, functioning in concert with other perceptual and conceptual systems.<br>
<font color="#1562c1"><br></font><b>09/01/13, 16h-18h</b><br><b>Lieu, ILPGA, 19 rue des bernardins, 75005, salle Mac</b></font></div><div><font face="Calibri"><b><br></b></font><div><div><div>
<div><div><font face="Calibri"><div><u><span style="text-align:center;">Center-embedded Sentences: A Phonological Challenge (</span><span style="text-align:center;">Joint research with Stefanie Nickels, McGill University)</span></u></div>
</font></div></div></div></div></div><font face="Calibri">Many explanations have been proposed for the extreme processing difficulty of doubly center-embedded relative clause (2CE-RC) constructions. We offer a phonological explanation. We maintain (i) that a sentence cannot be easily parsed and comprehended if it cannot be assigned a supportive prosodic contour, and (ii) that the flat structure of prosodic phrasing corresponds very poorly to the strongly hierarchical syntactic tree structure of 2CE-RC sentences.<br>
Sentence (1) is a commonly cited example in the literature. (2) is from the experimental materials of Gibson & Thomas (1999). Both are typically pronounced awkwardly, with ‘list intonation’. Assigning the requisite nested syntactic structure is so difficult that such sentences are often judged more grammatical when the second VP is (ungrammatically!) omitted, as in (3). This is the ‘missing VP illusion’. <br>
(1) The boy the dog the cat scratched bit died.<br>(2) The ancient manuscript that the grad student who the new card catalog had confused <br> a great deal was studying in the library was missing a page.<br>(3) *The ancient manuscript that the grad student who the new card catalog had <br>
confused a great deal was missing a page.<br>However, we find that the correct nested structure [NP1 [NP2 [NP3 VP1] VP2 ] VP3] can be facilitated by a prosodic phrasing which packages the center constituents (NP2 NP3 VP1 VP2) up together. Because there are length limits on prosodic phrases, this is feasible only if the center constituents are all short, and the outer constituents (NP1 and NP2) are each long enough to constitute a separate prosodic phrase. This is the case in (4). Both intuitively and as confirmed by our experimental data, examples like (4) are easier to pronounce and to understand than examples like (5), which has the same overall sentence length but has its weight in the wrong places: skinny outer constituents and fat inner ones.<br>
(4) The rusty old ceiling pipes that the plumber my dad trained fixed continue to leak <br> occasionally. <br>(5) The pipes that the unlicensed plumber the new janitor reluctantly assisted tried to <br>
repair burst.<br>It appears that the critical factor is avoidance of a prosody in which VP2 (tried to repair in (5)) breaks away as a separate prosodic phrase on its own. We believe the explanation for this is that syntax-prosody alignment is achieved by <u>syntactic</u> readjustment (Wagner 2010, Chomsky & Halle 1968, contra Selkirk 2000), creating a flatter tree structure. A prosodically separated VP2 would require (string-vacuous) extraposition of VP2 out of the relative clause it is in, but extraposition of a finite VP is illicit syntactically.<br>
<font color="#007329"><br></font><b>14/01/13, 14h-16h</b><br><b>Lieu: Université Paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div><div><font face="Calibri"><br></font><div><div>
<div><div><div><font face="Calibri"><u><span style="text-align:center;">A New Mis-fit Between Grammars and </span>Parser's<span style="text-align:center;"> </span></u></font></div></div></div>
</div></div><font face="Calibri">In early days of generative grammar, the study of sentence processing suffered a disappointment: the failure of the Derivational Theory of Complexity (DTC). The number of transformational rules applied in the syntactic derivation of a sentence did not predict how difficult it was to parse. Worse still, it proved impossible to reverse the transformational component so that it would derive the correct deep structure (hence meaning) from a surface word string. Reactions to this mismatch between the linguists’ grammar and the needs of sentence processing were varied. Some linguists (Bresnan; Gazdar et al.) responded by abandoning transformational rules, turning to grammar formalisms that deliver monostratal derivations that could run equally well in any direction. Efficiently functioning parsers for several languages have been developed in these frameworks over the years; see Abeillé (1988).<br>
Within the Transformational Grammar (TG) framework, psycholinguists responded to the DTC by abandoning the aim of using the grammar as a set of directions for processing. Instead (Wanner & Kaplan; Fodor) a surface string was processed as if it were a deep structure, until that failed due to a constituent not in its underlying position (a ‘filler’ such as a wh-phrase) or an obligatory constituent absent from the word string (a ‘gap’ or trace of movement); then the parser paired up fillers and gaps guided by some (ill-defined) consultation with grammatical constraints. Many experiments filled in details (anticipation of gaps, sensitivity to islands, etc.) but this general approach remained essentially unchanged throughout the period of Government-Binding Theory. <br>
With the advent of the Minimalist Program (MP) in the 1990s the situation worsened. One improvement from a psycholinguistic perspective was that syntactic derivations became monostratal, with movement (now copy-merge) interleaved with structure building operations. But movement and structure building were now both misaligned with sentence processing. This is because MP derivations inherently operate bottom-up, and at least in right-branching languages this means from right to left: starting at the end of a sentence. Again, a flurry of reactions to the problem. Fong (2005) created a filler-gap parser that computes MP structural representations but without direct use of an MP grammar. Chesi (2007) has reconfigured MP grammars so that they generate sentences top-down, left-to-right. Neeleman & van de Koot (2010) step away from the grammar/parser mis-fit by positing that both represent the same facts but at two different Marr-like levels of abstraction.<br>
>From the point of view of a working psycholinguist, I propose instead that the parser would build MP trees from interlocking chunks of tree structure, each chunk being the largest substructure introduced by one word of a sentence. Where do the chunks come from? The MP grammar generates complete sentential trees, which are then chopped up into these parser-friendly building blocks. One major problem remains, however. The tree chunks need to be informatively tagged so that they can be correctly stitched together by the parser, e.g., combining a chunk containing a filler with a chunk containing a gap. This is the case in other theories, such as HPSG; but in the Minimalist Program no node labels (except lexical ones) are permitted. <br>
<font color="#007329"><br></font><b>16/01/13, 16h-18h</b><br></font><div><div><div><div><div><div><font face="Calibri"><b>Lieu, ILPGA, 19 rue des bernardins, 75005, salle Mac</b></font></div>
</div></div><div><font face="Calibri"><br></font></div></div></div></div><font face="Calibri"><u>Disambiguating Triggers for Syntactic Parameters (<span style="text-align:center;">Joint work with William Sakas)</span></u><br>
Models of child language acquisition vary widely. Some presuppose innate guidance that permits rapid and largely error-free learning of syntax, while others assume statistical analysis of the linguistic input and/or trial-and-error procedures of various kinds. What type of model is capable of matching the achievements of child learners depends in large part on how ambiguous the input is with respect to the triggers (cues) for setting parameters. Ideally, each (non-default) parameter value would have an unambiguous trigger, a type of sentence uniquely compatible with that parameter setting. In reality, this seems unlikely to be true for the natural language domain. A simple example often noted: SVO word order is compatible with V2 (verb-second) grammars and with non-V2 grammars.<br>
We cannot – for obvious reasons – establish the extent of between-parameter ambiguity in the entire domain of natural languages: many of the languages in that domain are as yet unknown and unanalyzed. But we can approach the question by examining a constructed domain of languages, as much like natural languages as possible, but whose syntactic parameters and structural properties are all precisely specified. In our project, we created a domain of 3,072 languages characterized by 13 familiar syntactic parameters (head direction, null subject, etc.). We discovered unambiguous triggers for all of the non-default parameter values in all of the languages. However, in order to achieve this we had to posit a tool-kit of between-parameter priority relations to disambiguate triggers that otherwise would have been parametrically ambiguous. (This is similar to the findings of Dresher & Kaye, 1990, for phonological parameters.) The possible source of the priority relations then becomes a question of interest.<br>
</font></div><div><font face="Calibri"><br></font></div><div><font face="Calibri"><br></font></div><div><ul><li><font face="Calibri" size="5"><b><u>Irina Sekerina</u></b></font></li></ul><div><font face="Calibri"><b><br>
</b></font></div><font face="Calibri"><span><b>Associate Professor of Psychology, College of Staten Island</b></span><br><b><span style="color:rgb(59,59,59);"><u>Thème</u></span><span style="color:rgb(59,59,59);">: “Visual World Eye-Tracking: A Lifespan Perspective</span></b></font></div>
<div><font face="Calibri"><font color="#3b3b3b"><span><br></span></font><u>Dates :</u><br><b>07/01/13, 16h-18h</b><br><b>Lieu: Université paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div>
<div><font face="Calibri"><br></font><span style="font-family:Calibri;"><u>"Introduction:</u> the eye and eye movements, types of eye-trackers, eye movements in reading, Eye movements in speech: The visual World Eye-Tracking Paradigm (VWP), Practicalities of the VWP, Topics in the VWP research, The VWP Examaple: Spoken-word recognition"</span></div>
<div><font face="Calibri"><br><b>14/01/13, 16h-18h</b><br><b>Lieu: Université Paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div><div><font face="Calibri"><br></font><font face="Calibri"><u>"Children:</u> Development of eye-movement control in children, The Looking-While-Listening Paradigm, The VWP and development of processing strategies in children, Topics in the VWP research with children, The VWP and SLI children"<br>
<br><b>21/01/13, 16h-18h</b><br><b>Lieu: Université paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div><div><font face="Calibri"><br></font><font face="Calibri"><u>"People with Aphasia</u>: Spoken word recognition in aphasia, Processing of sentences with synthetic dependencies in aphasia"<br>
<br><b>28/01/13, 16h-18h</b><br><b>Lieu: Université Paris 7, 175 rue du Chevaleret, 75013, salle 4C92</b></font></div><div><font face="Calibri"><br><u>"Bilinguals:</u> Spoken word recognition in bilinguals (Russian-English, Dutch-English, French-English), Processing of grammatical gender in bilinguals (Spanish-English), Contrast and prosody in bilinguals (Russian-English)"<br>
Détail des séminaires en pj.<br></font></div><div></div><div></div><div><font face="Calibri"><br></font></div><br></div></div></div><br><br>
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font-size: 77%;
}
#reco-desc {
font-size: 77%;
}
.replbq {
margin: 4px;
}
#ygrp-actbar div a:first-child {
/* border-right: 0px solid #000;*/
margin-right: 2px;
padding-right: 5px;
}
#ygrp-mlmsg {
font-size: 13px;
font-family: Arial, helvetica,clean, sans-serif;
*font-size: small;
*font: x-small;
}
#ygrp-mlmsg table {
font-size: inherit;
font: 100%;
}
#ygrp-mlmsg select, input, textarea {
font: 99% Arial, Helvetica, clean, sans-serif;
}
#ygrp-mlmsg pre, code {
font:115% monospace;
*font-size:100%;
}
#ygrp-mlmsg * {
line-height: 1.22em;
}
#ygrp-mlmsg #logo {
padding-bottom: 10px;
}
#ygrp-mlmsg a {
color: #1E66AE;
}
#ygrp-msg p a {
font-family: Verdana;
}
#ygrp-msg p#attach-count span {
color: #1E66AE;
font-weight: 700;
}
#ygrp-reco #reco-head {
color: #ff7900;
font-weight: 700;
}
#ygrp-reco {
margin-bottom: 20px;
padding: 0px;
}
#ygrp-sponsor #ov li a {
font-size: 130%;
text-decoration: none;
}
#ygrp-sponsor #ov li {
font-size: 77%;
list-style-type: square;
padding: 6px 0;
}
#ygrp-sponsor #ov ul {
margin: 0;
padding: 0 0 0 8px;
}
#ygrp-text {
font-family: Georgia;
}
#ygrp-text p {
margin: 0 0 1em 0;
}
#ygrp-text tt {
font-size: 120%;
}
#ygrp-vital ul li:last-child {
border-right: none !important;
}
-->
</style>
</head>
<!--~-|**|PrettyHtmlEnd|**|-~-->
</html>
<!-- end group email -->