Doctoral Dissertation Research: The effect of social information on the perception of native- and nonnative-accented speech

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。在感知语音时，除了语音本身之外，听者还使用来自其环境的非语音信息。一个视觉线索，告知听众的讲话的理解是他们的看法说话者的种族。 这个博士论文改进资助项目研究了驱动这种效应的认知和语言机制。除了为语音处理的科学模型提供信息外，该项目的结果还可以揭示美国少数民族和/或将英语作为第二语言的英语使用者所面临的不平等。因此，这项工作可以作为一个重要的一步，解决和减少不平等的语言和种族biasies.This论文项目调查社会启动-社会信息如何影响语音感知-为本地和非本地口音的讲话。在一系列的实验中，全组的行为数据和个体差异数据相结合，以探讨社会启动效应的时程和特异性，它们与内隐种族协会的关系，以及它们对知觉适应非本地口音。为了确保对个体差异进行适当的检查，通过在线数据收集招募了大量参与者。转录任务用于评估受试者在背景噪声中理解目标句子的能力。为了研究对非母语口音的知觉适应，我们使用曲线拟合混合效应模型来估计实验过程中的表现。最终，这项跨学科工作的结果将提供语言和种族偏见如何影响人类处理语音的基础知识。该奖项反映了NSF的法定使命，并被认为值得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来支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). When perceiving speech, listeners use non-speech information from their environment in addition to the speech itself. One visual cue that informs listeners' understanding of speech is their perception of a talker's ethnicity. This doctoral dissertation improvement grant project examines the cognitive and linguistic mechanisms that drive this effect. In addition to informing scientific models of speech processing, the results of this project can shed light into the inequalities faced by speakers of English in the United States who belong to a minority race and/or speak English as a second language. This work can therefore serve as an important step toward addressing and reducing inequalities stemming from linguistic and racial biases.This dissertation project investigates social priming – how social information affects perception of speech – for both native- and nonnative-accented speech. In a series of experiments, group-wide behavioral data and individual differences data are integrated to examine the time-course and specificity of social priming effects, their relationship with implicit racial associations, and their effect on perceptual adaptation to nonnative accents. To ensure appropriate power for examination of individual differences, a large number of participants are recruited through online data collection. Transcription tasks are used to assess listeners' ability to understand target sentences presented in background noise. For the investigation of perceptual adaptation to nonnative accent, curve-fitting mixed-effects models are used to estimate performance over the course of the experiment. Ultimately, results of this interdisciplinary work will provide foundational knowledge of how linguistic and racial biases impact how humans process speech.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.