A B S T R A C TWhen we interact with one another, we tend to align our behaviors, including the way we talk. Psycholinguistic work has conceptualized alignment as the result of automatic cognitive mechanisms that operate to facilitate processing and communication. Sociolinguistic work has focused on the role of social identity and interactional strategy in explaining linguistic alignment. We draw on these two largely distinct traditions to investigate socially mediated syntactic alignment with the goal of understanding how social perception and cognition influence the mechanisms involved in alignment. A novel web-based paradigm was employed to collect speech data from a large socially heterogeneous sample. Participants listened to one of three speakers, each with a different accent, deliver an ideologically charged diatribe. Participants then completed a picture description task to assess the degree of syntactic alignment. Finally, participants completed a comprehensive social questionnaire designed to assess a wide range of social dimensions, which were tested as predictors of alignment. Our results suggest that syntactic alignment is to some extent automatic, but socially mediated. We found an overall alignment effect across social conditions and independent of social perceptions. However, the degree of alignment was influenced by a number of factors, including the perceived standardness of the passage speaker's accent, participants' perceived similarity to the speaker, and participants' preference for

The seeming ease with which we usually understand each other belies the complexity of the processes that underlie speech perception. One of the biggest computational challenges is that different talkers realize the same speech categories (e.g., /p/) in physically different ways. We review the mixture of processes that enable robust speech understanding across talkers despite this lack of invariance. These processes range from automatic pre-speech adjustments of the distribution of energy over acoustic frequencies (normalization) to implicit statistical learning of talker-specific properties (adaptation, perceptual recalibration) to the generalization of these patterns across groups of talkers (e.g., gender differences).

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Social and linguistic perceptions are linked. On one hand, talker identity affects speech perception. On the other hand, speech itself provides information about a talker's identity. Here, we propose that the same probabilistic knowledge might underlie both socially conditioned linguistic inferences and linguistically conditioned social inferences. Our computational-level approach-the ideal adapter-starts from the idea that listeners use probabilistic knowledge of covariation between social, linguistic, and acoustic cues in order to infer the most likely explanation of the speech signals they hear. As a first step toward understanding social inferences in this framework, we use a simple ideal observer model to show that it would be possible to infer aspects of a talker's identity using cue distributions based on actual speech production data. This suggests the possibility of a single formal framework for social and linguistic inferences and the interactions between them.

How fast can listeners adapt to unfamiliar foreign accents? Clarke and Garrett [J. Acoust. Soc. Am. 116, 3647-3658 (2004)] (CG04) reported that native-English listeners adapted to foreign-accented English within a minute, demonstrating improved processing of spoken words. In two web-based experiments that closely follow the design of CG04, the effects of rapid accent adaptation are examined and its generalization is explored across talkers. Experiment 1 replicated the core finding of CG04 that initial perceptual difficulty with foreign-accented speech can be attenuated rapidly by a brief period of exposure to an accented talker. Importantly, listeners showed both faster (replicating CG04) and more accurate (extending CG04) comprehension of this talker. Experiment 2 revealed evidence that such adaptation transferred to a different talker of a same accent. These results highlight the rapidity of short-term accent adaptation and raise new questions about the underlying mechanism. It is suggested that the web-based paradigm provides a useful tool for investigations in speech adaptation.

In summer 2017, Long Beach Unified School District partnered with Khan Academy to support pilot teachers in their implementation of Khan Academy in the classroom. This study examined how the use of Khan Academy in the middle school mathematics classroom relates to student achievement on the mathematics portion of the state standardized assessment. Results indicated that students who used Khan Academy for more than 30 minutes a week, the recommended usage time, scored an additional 22 points (0.20 standard deviation units) on the 2018 mathematics portion of the Smarter Balanced Assessment, compared to students who did not use Khan Academy. Additionally, these results hold true regardless of race/ethnicity, gender, eligibility for free/reduced lunch, or English learner status.

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