Abstract：
To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not sufficiently expressive for human languages. Combinatory categorial grammars (CCGs) are sufficiently expressive directly compositional models of grammar with flexible constituency that affords incremental interpretation. In this work, we evaluate whether a more expressive CCG provides a better model than a CFG for human neural signals collected with functional magnetic resonance imaging (fMRI) while participants listen to an audiobook story. We further test between variants of CCG that differ in how they handle optional adjuncts. These evaluations are carried out against a baseline that includes estimates of next-word predictability from a transformer neural network language model. Such a comparison reveals unique contributions of CCG structure-building predominantly in the left posterior temporal lobe: CCG-derived measures offer a superior fit to neural signals compared to those derived from a CFG. These effects are spatially distinct from bilateral superior temporal effects that are unique to predictability. Neural effects for structure-building are thus separable from predictability during naturalistic listening, and those effects are best characterized by a grammar whose expressive power is motivated on independent linguistic grounds.
摘要：
为了模拟自然主义环境中语言理解的行为和神经相关性，研究人员已经转向自然语言处理和机器学习领域的广泛工具。在明确建模句法结构的情况下，以前的工作主要依赖于上下文无关的语法(CFG)，然而，这种形式主义对人类语言来说表达不够。组合分类语法（CCG）是具有足够表达力的语法直接组成模型，具有灵活的组成成分，可以提供增量解释。在这项工作中,我们评估了在参与者听有声读物故事时,对于通过功能磁共振成像(fMRI)收集的人类神经信号,更具表现力的CCG是否提供了比CFG更好的模型.我们进一步测试了CCG的变体之间的差异，这些变体在它们如何处理可选的附属物方面有所不同。这些评估是针对基线进行的，该基线包括来自变压器神经网络语言模型的下一个单词可预测性的估计。这样的比较揭示了CCG结构构建主要在左颞叶后的独特贡献：与CFG衍生的测量相比，CCG衍生的测量提供了更好的神经信号拟合度。这些效应在空间上不同于可预测性独有的双边优越的时间效应。因此，结构建筑的神经效应与自然倾听过程中的可预测性是分开的，这些效果的最佳特征是语法，其表达能力是基于独立的语言依据。
