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首页> 外文期刊>Frontiers in Psychology >Experience-Based Probabilities Modulate Expectations in a Gender-Coded Artificial Language
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Experience-Based Probabilities Modulate Expectations in a Gender-Coded Artificial Language

机译:基于经验的概率以性别编码的人工语言调制期望

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The current study combines artificial language learning with visual world eyetracking to investigate acquisition of representations associating spoken words and visual referents using morphologically complex pseudowords. Pseudowords were constructed to consistently encode referential gender by means of suffixation for a set of imaginary figures that could be either male or female. During training, the frequency of exposure to pseudowords and their imaginary figure referents were manipulated such that a given word and its referent would be more likely to occur in either the masculine form or the feminine form, or both forms would be equally likely. Results show that these experience-based probabilities affect the formation of new representations to the extent that participants were faster at recognizing a referent whose gender was consistent with the induced expectation than a referent whose gender was inconsistent with this expectation. Disambiguating gender information available from the suffix did not mask the induced expectations. Eyetracking data provide additional evidence that such expectations surface during online lexical processing. Taken together, these findings indicate that experience-based information is accessible during the earliest stages of processing, and are consistent with the view that language comprehension depends on the activation of perceptual memory traces.
机译:当前的研究将人工语言学习与视觉世界眼动追踪相结合,以研究使用形态学复杂的伪单词将口语单词和视觉对象关联起来的表示形式的获取。伪字被构造为通过对一组可能是男性或女性的假想人物加后缀来一致地编码参照性别。在训练过程中,对伪单词及其假想图形对象的暴露频率进行了控制,以使给定的单词及其对象更可能以男性形式或女性形式出现,或者两种形式都同样可能出现。结果表明,这些基于经验的概率在某种程度上影响新表示的形成,即参与者识别性别与诱导期望相符的对象要比性别与期望相符的对象更快。可从后缀中消除性别信息的歧义并不能掩盖预期的结果。眼动追踪数据提供了其他证据,表明这种期望在在线词汇处理过程中浮出水面。综上所述,这些发现表明,基于经验的信息在处理的最早阶段是可访问的,并且与语言理解取决于感知记忆轨迹的激活这一观点是一致的。

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