BEGIN:VCALENDAR VERSION:2.0 PRODID:-//events.la.psu.edu//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:STANDARD DTSTART:20201101T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD BEGIN:DAYLIGHT DTSTART:20200308T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:16963-c43c6224d4ea8a5a145e41a0098fa8f8@events.la.psu.edu DTSTAMP:20260412T055005Z DTSTART;TZID=America/New_York:20220204T090000 DTEND;TZID=America/New_York:20220204T103000 SUMMARY:Heidi Getz (Georgetown) - Young Scholars Speaker Series DESCRIPTION:Sentence first\, arguments after: Mechanisms of morphosyntax acquisition\n\n Friday\, February 2nd\, 2022\, 9:00 am\, via Zoom. \n\n In natural languages\, there are complex patterns linking the structure of words (morphology) and the arrangement of words within sentences (syn tax). For example\, in German\, verbs in second position have different morphology than verbs in final position\, as in ‘dein Bruder möchte in d en Zoo gehen’ (“Your brother wants to go to the zoo”). In language acqui sition\, knowledge of this type of morphosyntactic contingency develops relatively early\, but we have very few mechanistic ideas about how lear ning takes place. \n\nIn this talk\, I explore the statistical learning mechanisms that underlie learning of morphosyntactic contingencies. I co ntrast two general approaches that a learner might take. One approach mi ght be to learn the position of prosodically prominent open-class words (“verbs go 2nd or last”) and then fill in the morphological details. Alt ernatively\, one could work in the opposite direction\, learning the pos ition of closed-class morphemes (“-te goes 2nd and -en goes last”) and f itting open-class items into the resulting structure. This second approa ch is counter-intuitive\, but I will argue that it is the one learners t ake. Evidence comes from a series of miniature language experiments with children and adults. In these experiments\, subtle mathematical distinc tions in learners’ input had significant effects on learning\, illuminat ing the biased statistical computations underlying distributional analys is. Taken together\, results suggest that learners organize knowledge of language patterns relative to a small set of closed-class items—just as patterns are represented in modern syntactic theory.\n\nFor more detail s: https://events.la.psu.edu/event/young-scholars-speaker-series-heidi-g etz-georgetown-university-medical-center/ X-ALT-DESC;FMTTYPE=text/html:

Sentence firs t, arguments after: Mechanisms of morphosyntax acquisition

 Friday, February 2nd, 2022, 9:00 am, via Zoom. < /span>

In natural languages, there are complex patterns linking the structure of words (morphology) and the arrangement of words within sentences (syn tax). For example, in German, verbs in second position have different mo rphology than verbs in final position, as in ‘dein Bruder möchte in den Zoo gehen’< /i> (“Your brother wants to go to the zoo”). In language acquisition, kn owledge of this type of morphosyntactic contingency develops relatively early, but we have very few mechanistic ideas about how learning takes p lace.

I n this talk, I explore the statistical learning mechanisms that underlie learning of morphosyntactic contingencies. I contrast two general appro aches that a learner might take. One approach might be to learn the posi tion of prosodically prominent open-class words (“verbs go 2nd or last”) and then fill in the morphological details. Alternatively, o ne could work in the opposite direction, learning the position of closed -class morphemes (“-te goes 2nd and -en goes la st”) and fitting open-class items into the resulting structure. This sec ond approach is counter-intuitive, but I will argue that it is the one l earners take. Evidence comes from a series of miniature language experim ents with children and adults. In these experiments, subtle mathematical distinctions in learners’ input had significant effects on learning, il luminating the biased statistical computations underlying distributional analysis. Taken together, results suggest that learners organize knowle dge of language patterns relative to a small set of closed-class items—j ust as patterns are represented in modern syntactic theory.

For more details: http s://events.la.psu.edu/event/young-scholars-speaker-series-heidi-getz-geo rgetown-university-medical-center/

END:VEVENT END:VCALENDAR