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FROM MOTHERESE TO ONE-WORD AND TWO-WORD CHILD LANGUAGE: A MULTIMODAL TEMPORAL CONNECTIONIST MODEL

机译:从母体到一词和两词的儿童语言:一种多模态的时间连接模型

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In this paper Hebbian based cross-situational learning is incorporated into a temporal hypermap to enable it to model the acquisition of early child language from child directed speech (CDS). This model exhibits the same level of performance as an earlier non-temporal, localist, Hebbian based cross-situational model by the same author when recalling one-word utterances from associated extralinguistic information. However, the performance of the temporal model is markedly better than the non-temporal model when required to generate appropriate one-word utterances when fed with the extralinguistic information of multi-word utterances in the training corpus. Given that cognitive processes such as child language acquisition are inherently temporal in nature, this suggests that incorporating temporal processing in cognitive models may improve the performance of these models.
机译:在本文中,基于Hebbian的跨情境学习被并入到时间超图中,以使其能够建模来自儿童定向语音(CDS)的早期儿童语言习得。当从相关的语言外信息中回忆一个单词的话语时,该模型表现出与同一作者基于早期非时间性,局部主义,基于Hebbian的跨情境模型相同的性能。但是,当在训练语料库中馈入多词话语的语言外信息时,如果需要生成适当的单词话语,则时态模型的性能明显优于非时态模型。考虑到诸如儿童语言习得之类的认知过程本质上是固有的时间性,这表明将时间处理纳入认知模型可以提高这些模型的性能。

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