Workshop: Learning Hidden Linguistic Structure; January 3-7, 2019, New York New York

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This workshop will bring together leading language researchers from two largely disjoint scientific communities: Linguistics and Natural Language Processing (NLP). The meeting will create a forum for intellectual exchange on linguistically oriented computational modeling and facilitate building of productive ties between the linguistics and NLP communities. To maximize the accessibility of the workshop to the broader linguistics community and to facilitate cross-disciplinary exchange, the workshop will take place in conjunction with the annual meeting of the Linguistic Society of America and will feature prominent invited speakers and panelists from the NLP community. Cross-disciplinary research that integrates principles of linguistics and findings from human language learning with cutting-edge computational methods from statistical machine learning promises to lead to scientific breakthroughs of mutual benefit to both research communities and to society more generally. Application of computational and mathematical modeling methods from NLP promises to enrich scientific understanding of the human language learning process and how it depends on the information present in children and adults' linguistic environments. The integration also has the potential to lead to new and improved language technologies, such as machine translation and automatic speech recognition systems that are playing an increasingly important role in modern society by facilitating communication between speakers of distinct languages, by increasing multilingual access to information and educational resources on the web, and by producing new tools and resources for people with speech, hearing, and language disabilities. In addition, the accessibility of the workshop to the broader linguistics community creates a pathway into STEM for women in linguistics that would not otherwise exist, providing educational, training and research connections with the NLP community.The theme for the workshop is "learning hidden linguistic structure", which is a topic chosen specifically because there are strong but largely separate research traditions approaching this fundamental learning problem in the two communities. Hidden structure is a common component of linguistic theories and of theories of human language learning, but much is still unknown about how such representations are learned by children from their linguistic input. On the other hand, NLP research has produced a wealth of computational techniques for modeling hidden structure and its learning, but these models rarely incorporate linguistic principles. Integrative research has the potential to lead to improvements in language technologies, especially in low-resource settings where success depends most on the capacity to generalize in linguistically appropriate ways from limited data. It also has potential to lead to scientific breakthroughs in understanding the sorts of computations and hidden representations that underlie human language learning. The workshop will host invited speakers who will present on the theme of "learning hidden linguistic structure" from interdisciplinary perspectives. To further increase ties between the linguistics and NLP communities, there will also be a special session with invited panelists on the topic of "What should linguists know about NLP? ". Finally, to facilitate the training of linguists in computational methods, the workshop will host two entry-level tutorials on machine learning methods in NLP.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.