Conference: Perceptrons and Syntactic Structures at 60: Computational Modeling of Language

本次研讨会将汇集认知科学和人工智能领域的顶尖研究人员，他们专门研究语言学理论与统计方法的整合，特别是神经网络。神经网络在语言技术（所谓的“深度学习”）的许多最新进展中都发挥了重要作用，将语言结构更大程度地整合到这些模型中，有望带来进一步的突破。本次会议的主要焦点将是如何将语言结构模型与概率学习理论相结合，从而更深入地了解人类处理和表示语言的方式。这种整合在过去很难实现，部分原因是每一种传统的研究人员被分离到不同的学科中，在不同的会议上相互作用。对人类语言结构的深入分析主要集中在语言学领域，而神经网络建模等统计学习研究主要集中在心理学和计算机科学领域。该研讨会将作为语言学计算学会成立大会的一部分举行，与美国语言学会的会议同时举行。因此，它将使其他学科的研究人员与语言学家接触，并将刺激富有成效的智力交流。

This workshop will bring together leading researchers in cognitive science and artificial intelligence who specialize in the integration of linguistic theory with statistical approaches, especially neural networks. Neural networks have been important in many of the recent advances in language technologies (in what's called "deep learning"), and the greater integration of linguistic structure into these models promises to lead to further breakthroughs. The main focus of this meeting will be on how integration of models of linguistic structure with probabilistic learning theories may lead to a deeper understanding of the way that humans process and represent language. This sort of integration has been difficult to achieve in the past in part because of the separation of researchers in each tradition into different disciplines interacting in different conferences. In-depth analysis of the structure of human languages is conducted in mostly in Linguistics, while neural network modeling and other statistical learning research is conducted mostly in Psychology and Computer Science. The workshop will be held as part of the inaugural meeting of the Society for Computation in Linguistics, taking place concurrently with the meeting of the Linguistic Society of America. It will thus bring researchers from other disciplines into contact with linguists, and will stimulate productive intellectual exchange.