Proceedings papers by Alex Fine
Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 2011
During incremental language understanding, comprehends draw on a rich base of probabilistic cues ... more During incremental language understanding, comprehends draw on a rich base of probabilistic cues to efficiently process the noisy perceptual input they receive. One challenge listeners face in employing such cues is that most cues are context dependent. Here, we present an experiment that investigates the extent to which listeners learn situation-specific adjustments in the information and/or weight of the lexical bias of a verb. Specifically, we ask to what extent comprehenders are able to rapidly change their interpretation of lexical cues to syntactic structure, where such behavior would be rational due to situation-specific statistics in the environment.
Papers by Alex Fine
Reflexive Orienting to Non- Predictive Gaze and Arrow Cues in Williams Syndrome
Frontiers in Human Neuroscience, 2009
Accounts of individual differences in on-line language processing ability often focus on the expl... more Accounts of individual differences in on-line language processing ability often focus on the explanatory utility of verbal working memory, as measured by reading span tasks. Although variability in reading span task performance likely reflects individual differences in multiple underlying traits, skills, and processes, accumulating evidence suggests that reading span scores also reflect variability in the linguistic experiences of an individual. Here, through an individual differences approach, we first demonstrate that reading span scores correlate significantly with measures of the amount of experience an individual has had with written language (gauged by measures that provide “proxy estimates” of print exposure). We then explore the relationship between reading span scores and on-line language processing ability. Individuals with higher
reading span demonstrated greater sensitivity to violations of statistical regularities found in natural language—as evinced by higher RTs on the disambiguating region of garden-path
sentences—relative to their lower span counterparts. This result held after statistically controlling for individual differences in a non-linguistic operation span task. Taken together, these results
suggest that accounts of individual differences in sentence processing can benefit from a stronger focus on experiential factors, especially when considered in relation to variability in perceptual and learning abilities that influence the amount of benefit gleaned from such experience.
During incremental language understanding, comprehenders draw on a rich base of probabilistic cue... more During incremental language understanding, comprehenders draw on a rich base of probabilistic cues to efficiently process the noisy perceptual input they receive. One challenge listeners face in employing such cues is that most cues are context-dependent. Here, we present an experiment that investigates the extent to which listeners learn situation-specific adjustments in the information and/or weight of the lexical bias of a verb. Specifically, we ask to what extent comprehenders are able to rapidly change their interpretation of lexical cues to syntactic structure, where such behavior would be rational due to situation-specific statistics in the environment.
Keywords: Language Comprehension; Ambiguity Resolution;
Learning Effects; Language Experience
As lifelong statistical learners, humans are remarkably sensitive to the unfolding of elements an... more As lifelong statistical learners, humans are remarkably sensitive to the unfolding of elements and events in their surroundings. In the present work, we examine the bi-directional influence of prediction-based processing and learning as adult participants were exposed to a visual artificial grammar containing a non-adjacent dependency. Using a self-paced moving window display, we recorded response times as learners progressed through a series of structured glyph sequences. After accounting for general task adaptation effects, we quantified the growing influence of element predictability on those response times. We find that, as a function of exposure, participants generally processed the grammar increasingly faster; however, the facilitatory benefit was significantly greater for the perfectly predictable items of the grammar. In turn, this progressive processing benefit on predictable elements was uniquely correlated with off-line performance on a post-test. Our results indicate that participants who develop implicit predictions as they learn, and have their expectations met, achieve higher learning outcomes. Links between these findings, obtained with novel stimuli in an experimental context, and the role of prediction in natural language comprehension are considered.
Language Learning, 2016
We present a new framework that conceptualizes language learning as a problem of hierarchical pro... more We present a new framework that conceptualizes language learning as a problem of hierarchical probabilistic inference under uncertainty, as motivated by recent work on native-language processing. We employ this framework to investigate the nature of transfer from prior language knowledge. The framework has two crucial components: statistical learning as one of the mechanisms through which adults acquire languages, and hierarchically structured representations of language knowledge. Furthermore, we propose that adults’ experience with previously learned languages shapes their beliefs about what linguistic structures are likely in any language. We argue that these prior beliefs guide the acquisition of additional languages: observations in the novel language are integrated with prior beliefs, incrementally adapting beliefs about both the novel
language and any language.
When we read or listen to language, we are faced with the challenge of inferring intended message... more When we read or listen to language, we are faced with the challenge of inferring intended messages from noisy input. This
challenge is exacerbated by considerable variability between and within speakers. Focusing on syntactic processing (parsing), we test the hypothesis that language comprehenders rapidly adapt to the syntactic statistics of novel linguistic environments (e.g., speakers or genres). Two self-paced reading experiments investigate changes in readers’ syntactic expectations based on repeated exposure to sentences with temporary syntactic ambiguities (so-called ‘‘garden path sentences’’). These sentences typically lead to a clear expectation violation signature when the temporary ambiguity is resolved to an a priori less expected structure (e.g., based on the statistics of the lexical context). We find that comprehenders rapidly adapt their syntactic expectations to converge towards the local statistics of novel environments. Specifically, repeated exposure to a priori unexpected structures can reduce, and even completely undo, their processing disadvantage (Experiment 1). The opposite is also observed: a priori expected structures become less expected (even eliciting garden paths) in environments where they are hardly ever observed (Experiment 2). Our findings suggest that, when changes in syntactic statistics are to be expected (e.g., when entering a novel environment), comprehends can rapidly adapt their expectations, thereby overcoming the processing disadvantage that mistaken expectations would otherwise cause. Our findings take a step towards unifying insights from research in expectation-based models of language processing, syntactic priming, and statistical learning.
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Proceedings papers by Alex Fine
Papers by Alex Fine
reading span demonstrated greater sensitivity to violations of statistical regularities found in natural language—as evinced by higher RTs on the disambiguating region of garden-path
sentences—relative to their lower span counterparts. This result held after statistically controlling for individual differences in a non-linguistic operation span task. Taken together, these results
suggest that accounts of individual differences in sentence processing can benefit from a stronger focus on experiential factors, especially when considered in relation to variability in perceptual and learning abilities that influence the amount of benefit gleaned from such experience.
Keywords: Language Comprehension; Ambiguity Resolution;
Learning Effects; Language Experience
language and any language.
challenge is exacerbated by considerable variability between and within speakers. Focusing on syntactic processing (parsing), we test the hypothesis that language comprehenders rapidly adapt to the syntactic statistics of novel linguistic environments (e.g., speakers or genres). Two self-paced reading experiments investigate changes in readers’ syntactic expectations based on repeated exposure to sentences with temporary syntactic ambiguities (so-called ‘‘garden path sentences’’). These sentences typically lead to a clear expectation violation signature when the temporary ambiguity is resolved to an a priori less expected structure (e.g., based on the statistics of the lexical context). We find that comprehenders rapidly adapt their syntactic expectations to converge towards the local statistics of novel environments. Specifically, repeated exposure to a priori unexpected structures can reduce, and even completely undo, their processing disadvantage (Experiment 1). The opposite is also observed: a priori expected structures become less expected (even eliciting garden paths) in environments where they are hardly ever observed (Experiment 2). Our findings suggest that, when changes in syntactic statistics are to be expected (e.g., when entering a novel environment), comprehends can rapidly adapt their expectations, thereby overcoming the processing disadvantage that mistaken expectations would otherwise cause. Our findings take a step towards unifying insights from research in expectation-based models of language processing, syntactic priming, and statistical learning.
reading span demonstrated greater sensitivity to violations of statistical regularities found in natural language—as evinced by higher RTs on the disambiguating region of garden-path
sentences—relative to their lower span counterparts. This result held after statistically controlling for individual differences in a non-linguistic operation span task. Taken together, these results
suggest that accounts of individual differences in sentence processing can benefit from a stronger focus on experiential factors, especially when considered in relation to variability in perceptual and learning abilities that influence the amount of benefit gleaned from such experience.
Keywords: Language Comprehension; Ambiguity Resolution;
Learning Effects; Language Experience
language and any language.
challenge is exacerbated by considerable variability between and within speakers. Focusing on syntactic processing (parsing), we test the hypothesis that language comprehenders rapidly adapt to the syntactic statistics of novel linguistic environments (e.g., speakers or genres). Two self-paced reading experiments investigate changes in readers’ syntactic expectations based on repeated exposure to sentences with temporary syntactic ambiguities (so-called ‘‘garden path sentences’’). These sentences typically lead to a clear expectation violation signature when the temporary ambiguity is resolved to an a priori less expected structure (e.g., based on the statistics of the lexical context). We find that comprehenders rapidly adapt their syntactic expectations to converge towards the local statistics of novel environments. Specifically, repeated exposure to a priori unexpected structures can reduce, and even completely undo, their processing disadvantage (Experiment 1). The opposite is also observed: a priori expected structures become less expected (even eliciting garden paths) in environments where they are hardly ever observed (Experiment 2). Our findings suggest that, when changes in syntactic statistics are to be expected (e.g., when entering a novel environment), comprehends can rapidly adapt their expectations, thereby overcoming the processing disadvantage that mistaken expectations would otherwise cause. Our findings take a step towards unifying insights from research in expectation-based models of language processing, syntactic priming, and statistical learning.