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Predicting the sources of impaired wh -question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.

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Title: Predicting the sources of impaired wh -question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.
Authors: Arslan, Seçkin (AUTHOR), Gür, Eren (AUTHOR), Felser, Claudia (AUTHOR)
Source: Cognitive Neuropsychology. Jul2017, Vol. 34 Issue 5, p312-331. 20p.
Subjects: Aphasia, Comprehension, Machine learning, Turkish language ability testing, German language ability testing
Abstract: This study investigates the comprehension ofwh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, awh-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 objectwhoand objectwhichquestions than to subject questions, while the German IWA performed better for subjectwhichquestions 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 ofwh-questions in aphasia. [ABSTRACT FROM AUTHOR]
Copyright of Cognitive Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Predicting the sources of impaired wh -question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.
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  Data: <searchLink fieldCode="AR" term="%22Arslan%2C+Seçkin%22">Arslan, Seçkin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gür%2C+Eren%22">Gür, Eren</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Felser%2C+Claudia%22">Felser, Claudia</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Cognitive+Neuropsychology%22">Cognitive Neuropsychology</searchLink>. Jul2017, Vol. 34 Issue 5, p312-331. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Aphasia%22">Aphasia</searchLink><br /><searchLink fieldCode="DE" term="%22Comprehension%22">Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Turkish+language+ability+testing%22">Turkish language ability testing</searchLink><br /><searchLink fieldCode="DE" term="%22German+language+ability+testing%22">German language ability testing</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study investigates the comprehension ofwh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, awh-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 objectwhoand objectwhichquestions than to subject questions, while the German IWA performed better for subjectwhichquestions 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 ofwh-questions in aphasia. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Cognitive Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1080/02643294.2017.1394284
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      – Code: eng
        Text: English
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        PageCount: 20
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      – SubjectFull: Aphasia
        Type: general
      – SubjectFull: Comprehension
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Turkish language ability testing
        Type: general
      – SubjectFull: German language ability testing
        Type: general
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      – TitleFull: Predicting the sources of impaired wh -question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.
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              Text: Jul2017
              Type: published
              Y: 2017
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