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Psycholinguistic norms for more than 300 lexical signs in German Sign Language (DGS)

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Trettenbrein,  Patrick
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Zaccarella,  Emiliano
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Trettenbrein, P., Pendzich, N.-K., Cramer, J.-M., Steinbach, M., & Zaccarella, E. (2021). Psycholinguistic norms for more than 300 lexical signs in German Sign Language (DGS). Behavior Research Methods, 53(5), 1817-1832. doi:10.3758/s13428-020-01524-y.


Cite as: https://hdl.handle.net/21.11116/0000-0007-93B7-4
Abstract
Sign language offers a unique perspective on the human faculty of language by illustrating that linguistic abilities are not bound to speech and writing. In studies of spoken and written language processing, lexical variables such as, for example, age of acquisition have been found to play an important role, but such information is not as yet available for German Sign Language (Deutsche Gebärdensprache, DGS). Here, we present a set of norms for frequency, age of acquisition, and iconicity for more than 300 lexical DGS signs, derived from subjective ratings by 32 deaf signers. We also provide additional norms for iconicity and transparency for the same set of signs derived from ratings by 30 hearing non-signers. In addition to empirical norming data, the dataset includes machine-readable information about a sign’s correspondence in German and English, as well as annotations of lexico-semantic and phonological properties: one-handed vs. two-handed, place of articulation, most likely lexical class, animacy, verb type, (potential) homonymy, and potential dialectal variation. Finally, we include information about sign onset and offset for all stimulus clips from automated motion-tracking data. All norms, stimulus clips, data, as well as code used for analysis are made available through the Open Science Framework in the hope that they may prove to be useful to other researchers: https://osf.io/mz8j4/