首页> 外文期刊>Cognitive science >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
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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

机译:直接与间接因果关系为语义语言通用:使用英语,希伯来语,印地文,日语和K'iche'mayan的计算模型预测巴厘岛的语法判断

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The aim of this study was to test the claim that languages universally employ morphosyntactic 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 native-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. A "random-semantics" model showed only a relatively small decrement in performance with seen verbs, whose behavior can be learned on a verb-by-verb basis, but achieved zero correlation with human judgments when generalizing to unseen verbs. Together, these findings suggest that Balinese conceptualizes directness of causation in a similar way to these unrelated languages, and therefore constitute support for the view that the distinction between more- versus less-distinct causation constitutes a morphosyntactic universal.
机译:本研究的目的是测试语言普遍使用形态学标记的声明,以区分更多 - 与较少直接的因果关系,更倾向于分别标记它们的少和更明显的标记(例如,有人打破了窗户Vs 。有人让窗户休息; *有人喊着这个男孩与某人让男孩哭泣)。为此,我们调查了最近的一个计算模型是否学会预测英语,希伯来语,印地,日语和K'Iche'Mayan中的两个造成者对两个造成者的讲话者相对偏好的偏好能够概括为第六语言它从未受过培训:巴厘岛。从48名母语的巴厘岛成年人收集了60个动词的相对可接受性的判断。复合跨语计算模型能够预测这些判断,不仅可以用于它所看到的动词,而且还可以在分裂半验证测试 - 以任何语言中从未见过的动词。 “随机语义”模型仅用所见的动词显示出相对较小的性能递减,其行为可以在动词的基础上学习,但是在推广到看不见的动词时,与人类判断的相关性归零。这些研究结果表明,巴厘岛的概念化了与这些无关语言类似的方式的因果关系,因此构成了对观点的支持,以至于更多地区的区别越来越明显的因果关系构成了语气交立普遍性。

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