Conference: Socially Situated Language Processing: Special Sessions at the Human Sentence Processing 2024 Conference

会议:社会情境语言处理:2024 年人类句子处理会议特别会议

基本信息

项目摘要

Research on how people produce and understand language has usually focused on situations with little social context, such as reading paragraphs and answering questions in highly controlled settings. But humans use language in an immense variety of social situations with others who differ from each other in factors like age, race/ethnicity, social class and more. These factors affect how humans use language. This award supports a special session at the 2024 meeting of the Society for Human Sentence Processing (SHSP) that brings together psychologists, linguists, neuroscientists and computer scientists to uncover how the human mind makes sense of language in socially rich and diverse situations. SHSP is a premiere scientific organization for the study of the mental processes involved in language use, and this special session helps to attract a more diverse set of scholars to the field—scholars whose participation is crucial for advancing this exciting science.The session is anchored by keynote presentations addressing questions such as: How does social information influence language understanding, production, and acquisition? How can language processing researchers engage more directly with language as it is practiced by and between socially diverse communities? These and other activities broaden the impact of sentence processing research by linking cognitive mechanisms, such as predictive processing and memory retrieval, with new perspectives from more natural and diverse contexts. The session promotes an expansion of the language varieties and language communities under investigation, including minoritized varieties that are only beginning to receive attention in language processing research. These efforts facilitate interdisciplinary training for junior scientists attending the conference through travel grants and outreach efforts to minority-serving institutions. The special session also contributes to broadening diversity in the STEM pipeline; centering research in diverse communities promotes the research of diverse scholars, attracts more diverse students, and offers opportunities for collaborations between scholars of different backgrounds.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.
关于人们如何产生和理解语言的研究通常集中在几乎没有社会背景的情况下,例如在高度受控的环境中阅读段落和回答问题,但人类在与其他因素不同的其他人之间使用语言。这些因素会影响人类使用语言的方式,该奖项支持人类句子处理学会 (SHSP) 2024 年会议的一次特别会议,该会议汇集了心理学家、语言学家和神经科学家。 SHSP 是研究语言使用心理过程的首要科学组织,本次特别会议有助于吸引更多不同的人。该领域的学者——他们的参与对于推动这一令人兴奋的科学至关重要。会议以主题演讲为基础,讨论以下问题:社会信息如何影响语言理解、产生和习得?语言处理研究人员如何更直接地参与其中?社会多元化社区之间所使用的语言?这些活动和其他活动通过将预测处理和记忆检索等认知机制与来自更自然和多样化背景的新视角联系起来,扩大了句子处理研究的影响。本次会议促进了所研究的语言品种和语言社区的扩展,包括。这些努力通过旅费资助和对少数族裔服务机构的推广工作,促进了参加会议的年轻科学家的跨学科培训,也有助于扩大 STEM 渠道的多样性;将研究集中在不同的社区促进多元化学者的研究,吸引更多元化的学生,并为不同背景的学者之间的合作提供机会。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Jonathan Brennan其他文献

Supplemental Material for “Hierarchical structure guides rapid linguistic predictions during naturalistic listening”
“层次结构指导自然听力期间的快速语言预测”的补充材料
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jonathan Brennan;J. Hale
  • 通讯作者:
    J. Hale
The Cambridge Handbook of Biolinguistics: Grounding the cognitive neuroscience of semantics in linguistic theory
剑桥生物语言学手册:在语言理论中奠定语义认知神经科学的基础
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    L. Pylkkänen;Jonathan Brennan;D. Bemis
  • 通讯作者:
    D. Bemis
Neural correlates of object-extracted relative clause processing across English and Chinese
英汉宾语提取关系从句处理的神经关联
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Donald Dunagan;Miloš Stanojević;Maximin Coavoux;Shulin Zhang;Shohini Bhattasali;Jixing Li;Jonathan Brennan;John Hale
  • 通讯作者:
    John Hale
How do Listeners Form Grammatical Expectations to African American Language
听众如何对非裔美国语言形成语法期望
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Rachel Elizabeth Weissler;Jonathan Brennan
  • 通讯作者:
    Jonathan Brennan
Modeling Incremental Language Comprehension in the Brain with Combinatory Categorial Grammar
用组合范畴语法对大脑中的渐进语言理解进行建模
  • DOI:
    10.18653/v1/2021.cmcl-1.3
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    5.3
  • 作者:
    Miloš Stanojević;Shohini Bhattasali;Donald Dunagan;Luca Campanelli;Mark Steedman;Jonathan Brennan;John Hale
  • 通讯作者:
    John Hale

Jonathan Brennan的其他文献

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{{ truncateString('Jonathan Brennan', 18)}}的其他基金

US-French Collaboration: Collaborative Research: Neuro-Computational Models of Natural Language
美法合作:合作研究:自然语言的神经计算模型
  • 批准号:
    1607251
  • 财政年份:
    2016
  • 资助金额:
    $ 6.24万
  • 项目类别:
    Continuing Grant

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