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Predicting the sources of impaired wh-question comprehension in non-fluent aphasia

  • This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-pointing tasks. Findings from our experiments show that the Turkish IWA responded more accurately to both object who and object which questions than to subject questions, while the German IWA performed better for subject which questions than in all other conditions. Using random forest models, a machine learning technique used in tree-structured classification, on the individual data revealed that both the Turkish and German IWA’s response accuracy is largely predicted by the presence of overt and unambiguous case marking. We discuss our results with regard to different theoretical approaches to the comprehension of wh-questions in aphasia.

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Author:Seçkin ArslanORCiD, Eren Gür, Claudia FelserORCiDGND
Parent Title (English):Postprints der Universität Potsdam : Humanwissenschaftliche Reihe
Subtitle (English):a cross-linguistic machine learning study on Turkish and German
Series (Serial Number):Postprints der Universität Potsdam : Humanwissenschaftliche Reihe (464)
Document Type:Postprint
Date of first Publication:2018/08/07
Year of Completion:2017
Publishing Institution:Universität Potsdam
Release Date:2018/08/07
Tag:Non-fluent aphasia; random forest algorithm; sentence comprehension; wh-in-situ; wh-movement; wh-questions
Source:Cognitive Neuropsychology 34 (2017) Nr. 5, S. 312–331 DOI: 10.1080/02643294.2017.1394284
Organizational units:Humanwissenschaftliche Fakultät
Dewey Decimal Classification:1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
4 Sprache / 40 Sprache / 400 Sprache
Peer Review:Referiert
Publication Way:Open Access
Grantor:Taylor & Francis Open Access Agreement
Licence (German):License LogoCreative Commons - Namensnennung, Nicht kommerziell, Keine Bearbeitung 4.0 International