CAREER: Tracking correlation or inferring causation: How human language processing adapts to the environment

职业：跟踪相关性或推断因果关系：人类语言处理如何适应环境

• 批准号: 2336304
• 负责人: Rachel Ryskin
• 金额: $ 67.42万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2029-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2336304&HistoricalAwards=false
• 关键词: CAREER; Tracking; correlation; inferring; causation

When people converse face-to-face, on the phone, or by video conference, the signal is often noisy and incomplete. Luckily, communication usually still proceeds smoothly because listeners can use other sources of information (the context, visual cues, etc.) to make rational inferences about what the speaker said. This CAREER award aims to expand our theoretical understanding of this process and refine existing computational accounts, by investigating how listeners flexibly adapt their inferences and expectations in different contexts. For example, how do adults adapt their expectations when speaking with a child rather than with another adult or when speaking with other adults with different accents? Results of this work will advance knowledge of the cognitive processes that enable human communication and may have important implications for the development of technologies that support human-to-human or human-to-AI conversations. The PI is in a Hispanic-Serving Institution and plans to broaden participation in STEM science on multiple scales, from one-on-one mentorship of undergraduates to an upper-level undergraduate course and an outreach talk series.The project investigates how listeners flexibly adapt to different contexts (e.g., different speakers/environments), within the perspective of human communication as rational inference under uncertain input. Two possible mechanisms are that listeners track correlations in the environment or that they deploy and update a causal model of the speaker and transmission process. A series of eye-tracking experiments, paired with computational simulations, will capture the inferences that listeners make “on the fly,” when listening to speech. How listeners learn and adjust their representations to the context will be probed by varying the nature and quantity of errors and noise.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.

当人们面对面，通过电话或视频会议面对面时，信号通常是噪音和不完整的。幸运的是，沟通通常仍然顺利进行，因为听众可以使用其他信息来源（上下文，视觉提示等）来制作有关说话者所说的理性信息。该职业奖旨在通过调查听众如何在不同情况下灵活地调整其推论和期望来扩展我们对这一过程的理论理解并完善现有的计算帐户。例如，成年人在与孩子交谈时，与其他成年人交谈时，或与其他带有不同口音的成年人交谈时，如何适应自己的期望？这项工作的结果将促进了解能够使人​​类交流的认知过程的知识，并可能对支持人类到人类或人向人类对话的技术的发展具有重要意义。 PI处于西班牙裔服务机构中，并计划在多个范围内扩大参与STEM科学的参与，从本科生的一对一心态到高级本科课程和外展谈话系列。该项目调查了听众如何灵活地适应不同的环境（例如，不同的讲话者/环境）（在不同的语言环境中），而在人类的沟通中，这是在与人类交流中的范围。两种可能的机制是听众跟踪环境中的相关性，或者他们部署并更新了扬声器和传输过程的灾难性模型。一系列引人注目的追踪实验与计算模拟配对，将捕获听众在听语音时“飞行”的推论。听众如何通过改变错误和噪声的性质和数量来探讨听众的表现方式。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。