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Vortrag von Artemis Alexiadou am Dienstag, 25.04.2017 (16:00 Uhr - GB 3/159)

Montag, 10. April 2017. Aus der Kategorie 'Vortragsreihe'.

Das Sprachwissenschaftliche Institut lädt herzlich ein zum Vortrag von

Artemis Alexiadou  
(Humboldt-Universität zu Berlin & Leibniz-Zentrum Allgemeine Sprachwissenschaft (ZAS))

The many faces of plural.

mehr

Vortrag von Heike Zinsmeister am Dienstag, 07.02.2017 (16:00 Uhr - GB 3/159)

Freitag, 03. Februar 2017. Aus der Kategorie 'Vortragsreihe'.

Das Sprachwissenschaftliche Institut lädt herzlich ein zum Vortrag von

Heike Zinsmeister (Universität Hamburg)

Zur Funktion und Resolution von nicht-nominalen Anaphern.

mehr

Vortrag von Maria Rauschenberger am Dienstag, 24.01.2017 (16:00 Uhr - GB 3/159)

Donnerstag, 05. Januar 2017. Aus der Kategorie 'Vortragsreihe'.

Das Sprachwissenschaftliche Institut lädt herzlich ein zum Vortrag von

Maria Rauschenberger (Universitat Pompeu Fabra, Barcelona)

Detection and intervention of Dyslexia

mehr

Vortrag von Patrick Rebuschat am Dienstag, 10.01.2017 (16:00 Uhr - GB 3/159)

Mittwoch, 14. Dezember 2016. Aus der Kategorie 'Vortragsreihe'.

Das Sprachwissenschaftliche Institut lädt herzlich ein zum Vortrag von

Patrick Rebuschat (Lancaster University)

Implicit-statistical learning of words and syntax: Evidence from cross-situational learning

In this talk, I will present recent experiments that bring together methodological insights from two related, yet completely distinct research strands, namely “implicit learning” (Reber, 1967) and “statistical learning” (e.g., Saffran et al, 1996). In the first part, I will discuss experiments that used verbal reports and subjective measures of awareness to determine what strategies subjects followed in the learning task and whether they became aware of rules or patterns. Results indicate that provision of prior (explicit) knowledge significantly boosts implicit-statistical learning. In the second part, I will introduce a novel artificial language paradigm that is part of a long-term project on individual differences in language learning across the lifespan. Our results demonstrate that adult learners can simultaneously acquire lexical and syntactic information by keeping track of cross-trial statistics, after brief exposure, without feedback and without the conscious intention to learn. We conclude by discussing implications for future research.

Vortrag von Sabine Schulte im Walde am Dienstag, 06.12.2016 (16:00 Uhr - GB 3/159)

Montag, 28. November 2016. Aus der Kategorie 'Vortragsreihe'.

Das Sprachwissenschaftliche Institut lädt herzlich ein zum Vortrag von

Sabine Schulte im Walde (Universität Stuttgart)

Distributional approaches to semantic relatedness

Distributional models assume that the contexts of a linguistic unit (such as a word, a multi-word expression, a phrase, a sentence, etc.) provide information about the meaning of the linguistic unit (Harris, 1954, Firth, 1957). They have been widely applied in data-intensive lexical semantics (among other areas), and proven successful in diverse research issues, such as the representation and disambiguation of word senses; selectional preference modelling; the compositionality of compounds and phrases, or as a general framework across semantic tasks.

While it is clear that distributional knowledge does not cover all the cognitive knowledge humans possess with respect to word meaning (Marconi, 1997; Lenci, 2008), distributional models are very attractive, as the underlying parameters are accessible from even low-level annotated corpus data. We are thus interested in maximizing the benefit of distributional information for lexical semantics, by exploring the meaning and the potential of comparatively simple distributional models.

In this respect, this talk will present four case studies on semantic relatedness tasks that demonstrate the potential and the limits of distributional models: (i) the availability of various German association norms in standard web and newspaper corpora; (ii) the prediction of compositionality for German multi-word expressions; (iii) the distinction between the paradigmatic relations synonymy, antonymy and hypernymy with regard to German nouns, verbs and adjectives; and (iv) the integration and evaluation of distributional semantic information into an SMT system.