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Toward a New Scientific Visualization for the Language Sciences

机译:走向语言科学的新科学可视化

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All scientists use data visualizations to discover patterns in their phenomena that may have otherwise gone unnoticed. Likewise, we also use scientific visualizations to help us describe our verbal theories and predict those data patterns. But scientific visualization may also constitute a hindrance to theory development when new data cannot be accommodated by the current dominant framework. Here we argue that the sciences of language are currently in an interim stage using an increasingly outdated scientific visualization borrowed from the box-and-arrow flow charts of the early days of engineering and computer science. The original (and not yet fully discarded) version of this obsolete model assumes that the language faculty is composed of autonomously organized levels of linguistic representation, which in turn are assumed to be modular, organized in rank order of dominance, and feed unidirectionally into one another in stage-like algorithmic procedures. We review relevant literature in psycholinguistics and language acquisition that cannot be accommodated by the received model. Both learning and processing of language in children and adults, at various putative ‘levels’ of representation, appear to be highly integrated and interdependent, and function simultaneously rather than sequentially. The fact that half of the field sees these findings as trivially true and the other half argues fiercely against them suggests to us that the sciences of language are on the brink of a paradigm shift. We submit a new scientific visualization for language, in which stacked levels of linguistic representation are replaced by trajectories in a multidimensional space. This is not a mere redescription. Processing language in the brain equates to traversing such a space in regions afforded by multiple probabilistic cues that simultaneously activate different linguistic representations. Much still needs to be done to convert this scientific visualization into actual implemented models, but at present it allows language scientists to envision new concepts and venues for research that may assist the field in transitioning to a new conceptualization, and provide a clear direction for the next decade.
机译:所有科学家都使用数据可视化来发现其现象的模式,这些模式本来可能不会引起注意。同样,我们还使用科学的可视化来帮助我们描述口头理论并预测这些数据模式。但是,当当前主导框架无法容纳新数据时,科学可视化也可能成为理论发展的障碍。在这里,我们认为,语言科学目前处于过渡阶段,它使用了从工程学和计算机科学的早期方框图和箭头流程图中借来的越来越过时的科学可视化效果。此过时的模型的原始版本(但尚未完全废弃)是假定语言系由自主组织的语言表示层组成,而这些语言表示层又被认为是模块化的,按支配地位的等级进行组织,并单向馈入另一个类似阶段的算法过程。我们回顾了心理语言学和语言习得中的相关文献,这些文献不能被所接收的模型容纳。儿童和成人的语言学习和处理,在各种假定的“代表”水平上,似乎都是高度整合和相互依存的,并且同时而非顺序地起作用。该领域的一半认为这些发现微不足道,而另一半则强烈反对它们,这一事实向我们表明,语言科学正处于范式转变的边缘。我们提交了一种新的语言科学可视化方法,其中用多层空间中的轨迹代替了堆叠的语言表示形式。这不仅是重新描述。大脑中的处理语言等同于遍历多个概率线索提供的区域中的此类空间,这些线索同时激活了不同的语言表示形式。要将科学的可视化转换为实际实现的模型仍然需要做很多工作,但是目前,它使语言科学家可以设想新的概念和研究场所,这可能有助于该领域过渡到新的概念化,并为语言学家提供明确的方向。下个十年。

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