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Language play facilitates language learning: Optimizing the input for gender-like category induction

机译:语言游戏可促进语言学习:优化输入以进行类似性别的类别归纳

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摘要

Gender induction has been claimed to be virtually impossible unless nouns provide reliable semantic or phonological gender-relevant cues. However, learners might exploit syntactic cues, such as definite articles, to infer the gender of gender-unmarked nouns. In children’s poems and songs, such syntactic cues are presented in a highly structured fashion. We assessed gender-like category induction in an artificial language that provided exclusively syntactic cues for its gender-like subclasses. We trained participants with structured or unstructured input presented in a prose, a rhyming, a melodic, or a rhyming and melodic fashion. Input structuring significantly facilitated gender-like category induction. Participants trained in the Rhyme-and-Melody mode significantly outperformed participants trained in the Prose mode, especially when the input was structured. The Rhyme-only and Melody-only modes yielded intermediate results. Thus, a highly structured rhyming and melodic input substantially facilitates gender-like category induction, making a case for the use of children’s songs in language teaching.
机译:除非名词提供可靠的语义或语音相关性别暗示,否则实际上几乎不可能进行性别归纳。但是,学习者可能会利用语法提示(例如定冠词)来推断未标记性别的名词的性别。在儿童的诗歌和歌曲中,这种语法提示以高度结构化的方式呈现。我们使用人工语言评估了类似性别的类别归纳,该人工语言仅为其性别类的子类提供了语法提示。我们以散文,押韵,旋律或押韵和旋律的方式对结构化或非结构化输入进行了培训。投入结构显着促进了类似性别的类别归纳。在“韵律和旋律”模式下训练的参与者明显优于在“散文”模式下训练的参与者,尤其是在构建输入时。仅押韵和仅旋律模式产生中间结果。因此,高度结构化的押韵和旋律输入会极大地促进类似性别的类别归纳,从而为在语言教学中使用儿童歌曲提供了依据。

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