scholarly journals Direct Versus Indirect Causation as a Semantic Linguistic Universal: Using a Computational Model of English, Hebrew, Hindi, Japanese, and K'iche’ Mayan to Predict Grammaticality Judgments in Balinese

2021 ◽  
Vol 45 (4) ◽  
Author(s):  
I Nyoman Aryawibawa ◽  
Yana Qomariana ◽  
Ketut Artawa ◽  
Ben Ambridge
Keyword(s):  
Computational Model ◽  
Grammaticality Judgments ◽  
Linguistic Universal

scholarly journals Direct versus indirect causation as a semantic linguistic universal: Using a computational model of English, Hebrew, Hindi, Japanese and K’iche’ Mayan to predict grammaticality judgments in Balinese.

2020 ◽  
Author(s):  
Ben Ambridge
Keyword(s):  
Computational Model ◽  
Validation Test ◽  
Relative Preference ◽  
Grammaticality Judgments ◽  
Direct Causation ◽  
Linguistic Universal

The aim of this study was to test the claim that languages universally employmorphosyntactic marking to differentiate events of more- versus less-direct causation,preferring to mark them with less- and more- overt marking respectively (e.g., Somebody broke the window vs Somebody MADE the window break; *Somebody cried the boy vs Somebody MADE the boy cry). To this end, we investigated whether a recent computational model which learns to predict speakers’ by-verb relative preference for the two causatives in English, Hebrew, Hindi, Japanese and K’iche’ Mayan is able to generalize to a sixth language on which it has never been trained: Balinese. Judgments of the relative acceptability of the less- and more-transparent causative forms of 60 verbs were collected from 48 nativ speaking Balinese adults. The composite crosslinguistic computational model was able to predict these judgments, not only for verbs that it had seen, but also – in a split-half validation test – to verbs that it had never seen in any language. Clearly, this is only possible if Balinese conceptualizes directness of causation in a similar way to these unrelated languages. Thus, the present findings constitute support for the view that the distinction between more- versus less-distinct causation constitutes a morphosyntactic universal.

Inference making and memory for text: A computational model

2001 ◽  
Author(s):  
Paul Van Den Broek ◽  
Yuhtsuen Tzeng ◽  
Sandy Virtue ◽  
Tracy Linderholm ◽  
Michael E. Young
Keyword(s):  
Computational Model ◽  
Inference Making ◽  
Memory For Text

Computational Model of Novel Popout

1992 ◽  
Author(s):  
William A. Johnston ◽  
Kevin J. Hawley ◽  
James M. Farnham
Keyword(s):  
Computational Model
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