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A hybrid neural network and virtual reality system for spatial language processing

机译:用于空间语言处理的混合神经网络和虚拟现实系统

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Describes a neural network model for the study of spatial language. It deals with both geometric and functional variables, which have been shown to play an important role in the comprehension of spatial prepositions. The network is integrated with a virtual reality interface for the direct manipulation of geometric and functional factors. The training uses experimental stimuli and data. Results show that the networks reach low training and generalization errors. Cluster analyses of hidden activation show that stimuli primarily group according to extra-geometrical variables.
机译:描述了用于空间语言研究的神经网络模型。它涉及几何和功能变量,这已被证明在理解空间介词中起着重要的作用。该网络与虚拟现实界面集成在一起,可直接操纵几何和功能因素。培训使用实验性刺激和数据。结果表明,该网络达到较低的训练和泛化误差。隐藏激活的聚类分析表明,刺激主要根据几何外变量进行分组。

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