Learning the Causative Alternation in English and Japanese Speakers: Statistical and Non-statistical Effects

Learning the Causative Alternation in English and Japanese Speakers: Statistical and Non-statistical Effects
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学习英语和日语使用者的使役交替:统计和非统计效应

DOI:
10.1080/15475441.2019.1645667
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发表时间:
2019
影响因子:
1.5
通讯作者:
Suzuki Yuichi
Suzuki Yuichi
中科院分区:
人文科学4区
文献类型:
--
作者:
Huang Yi Ting;Bounds Mary;Suzuki Yuichi

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儿童通过分布证据获得论元结构,但这如何与事件语义和现有的动词知识相互作用?目前的研究比较了日语(词汇使役跨越更广泛的语义类别)和英语(交替更受限制)的成年人的动词学习。在完全交替熟悉中,新动词在及物和不及物框架中分别发生了内部原因事件(类似于decline)和外部原因事件(类似于roock)。在半交替熟悉法中,内因事件只发生在不及物动词中,而外因事件则同时发生在两个框架中。在测试过程中,参与者对所有事件的传递性和不传递性描述的自然性进行评级。对于内部引起的事件,在半交替熟悉(只包括不及物动词)之后,及物动词在所有发言者中的评分都相当低,而不及物动词对英语的适应性比日语更好。对于外部引起的事件,所有的参与者都认为及物动词高于不及物动词,尽管在熟悉的情况下发生率相同。这可能与场景中存在显著的有生命的代理有关。总之,这表明,句法和语义偏见同时影响分布证据的解释。通过现有的句法表示来解释输入统计数据,并且显著的语义差异可能会对句法实例产生偏见。
Children acquire argument structure through distributional evidence, but how does this interacts with event semantics and existing verb knowledge? The current study compares verb learning in adult speakers of Japanese (where lexical causatives span wider semantic categories) and English (where alternation is more restricted). In the Fully alternating familiarization, internally caused events (similar todescend) and externally caused events (similar torock) occurred with novel verbs in transitive and intransitive frames. In the Semi-alternating familiarization, internally caused events occurred with intransitives only while externally caused events occurred with both frames. During the test, participants rated the naturalness of transitive and intransitive descriptions for all events. For internally caused events, transitives were rated equivalently low across speakers after the Semi-alternating familiarization (which featured only intransitives), while intransitives were more felicitous for English compared to Japanese speakers. For externally caused events, all participants rated transitives higher than intransitives, despite equal occurrence across familiarizations. This may be related to the presence of salient animate agents in scenes. Together, this suggests that syntactic and semantic biases concurrently influence the interpretation of distributional evidence. Input statistics are interpreted through existing syntactic representations, and salient semantic distinctions may exert a bias for syntactic instantiations.
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