Stewart McCauley | The University of Iowa (original) (raw)

Papers by Stewart McCauley

Developmental Science, 2021

Data availability statement: This study involved the analysis of a publicly available dataset. A ... more Data availability statement: This study involved the analysis of a publicly available dataset. A URL for analysis code is provided in the main text. Acknowledgments: This work was supported by the International Centre for Language and Communicative Development (LuCiD). The support of the Economic and Social Research Council [ES/L008955/1] is gratefully acknowledged. We are grateful to Julian Pine for valuable comments on an earlier version of the manuscript. Multiword units lead to errors of commission in children's spontaneous production: "What corpus data can tell us?*" Research Highlights • Recent decades have seen mounting evidence that children are sensitive to the properties (e.g., frequency) of compositional word sequences. • Previous research has focused on the role of multiword units in protecting against errors of omission. • By analyzing wh-questions appearing in children's spontaneous productions, we find the first evidence that the global input frequency of multiword sequences is a predictor of their errorful appearance, or intrusion into utterances. • Our finding that multiword units can shape errors of commission constitutes particularly powerful evidence that such sequences constitute linguistic units in their own right.

Proceedings of the 41st Annual Conference of the Cognitive Science Society, 2019

A central question for cognitive science is whether children's linguistic productivity can be cap... more A central question for cognitive science is whether children's linguistic productivity can be captured by item-based learning, or whether the learner must be guided by abstract, system-wide principles governed by innate constraints. Here, we present a computational model of early language acquisition which learns to discover and use lexically-based frames in a fully incremental, on-line fashion. The model is rooted in simple prediction-and recognition-based processes, subject to the same memory limitations as language learners. When exposed to English corpora of child-directed speech, the model is able learn developmentally plausible frames and use them to capture over 70% of the utterances produced by target children aged 2 to 5. Across a typologically diverse range of 29 languages, the model is able to capture over 68% of child utterances. Together, these findings suggest that much of children's early linguistic productivity can be captured by item-based learning through computationally simple mechanisms.

Proceedings of the 41st Annual Conference of the Cognitive Science Society, 2019

Subject-auxiliary inversion in interrogatives has been a topic of great interest in language acqu... more Subject-auxiliary inversion in interrogatives has been a topic of great interest in language acquisition research, and has often been held up as evidence for the structure-dependence of grammar. Usage-based and nativist approaches posit different representations and processes underlying children's question formation and therefore predict different causes for these errors. Here, we explore the question of whether input statistics predict children's spontaneous non-inversion errors with wh-questions. In contrast to previous studies, we look at properties of the non-inverted, errorful forms of questions. Through a series of corpus analyses, we show that the frequency of uninverted subsequences (e.g., "she is going" in "what she is going to do?*") is a good predictor of children's errors, consistent with recent evidence for multiword units in children's comprehension and production. This finding has implications for the types of mental representations and cognitive processes researchers ascribe to children acquiring a first language.

Psychological Review, 2019

While usage-based approaches to language development enjoy considerable support from computationa... more While usage-based approaches to language development enjoy considerable support from computational studies, there have been few attempts to answer a key computational challenge posed by usage-based theory: the successful modeling of language learning as language use. We present a usage-based computational model of language acquisition which learns in a purely incremental fashion, through online processing based on chunking, and which offers broad, cross-linguistic coverage while uniting key aspects of comprehension and production within a single framework. The model's design reflects memory constraints imposed by the real-time nature of language processing, and is inspired by psycholinguistic evidence for children's sensitivity to the distributional properties of multiword sequences and for shallow language comprehension based on local information. It learns from corpora of child-directed speech, chunking incoming words together to incrementally build an item-based "shallow parse." When the model encounters an utterance made by the target child, it attempts to generate an identical utterance using the same chunks and statistics involved during comprehension. High performance is achieved on both comprehension-and production-related tasks: the model's shallow parsing is evaluated across 79 single-child corpora spanning English, French, and German, while its production performance is evaluated across over 200 single-child corpora representing 29 languages from the CHILDES database. The model also succeeds in capturing findings from children's production of complex sentence types. Together, our modeling results suggest that much of children's early linguistic behavior may be supported by item-based learning through online processing of simple distributional cues, consistent with the notion that acquisition can be understood as learning to process language.

Attempts to connect individual differences in statistical learning with broader aspects of cognit... more Attempts to connect individual differences in statistical learning with broader aspects of cognition have received considerable attention, but have yielded mixed results. A possible explanation is that statistical learning is typically tested using the two-alternative forced choice (2AFC) task. As a meta-cognitive task relying on explicit familiarity judgments, 2AFC may not accurately capture implicitly formed statistical computations. In this paper, we adapt the classic serial-recall memory paradigm to implicitly test statistical learning in a statistically-induced chunking recall (SICR) task. We hypothesized that artificial language exposure would lead subjects to chunk recurring statistical patterns, facilitating recall of words from the input. Experiment 1 demonstrates that SICR offers more fine-grained insights into individual differences in statistical learning than 2AFC. Experiment 2 shows that SICR has higher test-retest reliability than that reported for 2AFC. Thus, SICR offers a more sensitive measure of individual differences, suggesting that basic chunking abilities may explain statistical learning.

Several recent empirical findings have reinforced the notion that a basic learning and memory ski... more Several recent empirical findings have reinforced the notion that a basic learning and memory skill—chunking—plays a fundamental role in language processing. Here, we provide evidence that chunking shapes sentence processing at multiple levels of linguistic abstraction, consistent with a recent theoretical proposal by Christiansen and Chater (2016). Individual differences in chunking ability at two different levels is shown to predict on-line sentence processing in separate ways: i) phonological chunking ability, as assessed by a variation on the non-word repetition task, predicts processing of complex sentences featuring phonological overlap; ii) multiword chunking ability, as assessed by a variation on the serial recall task, is shown to predict reading times for sentences featuring long-distance number agreement with locally distracting number-marked nouns. Together, our findings suggest that individual differences in chunking ability shape language processing at multiple levels of abstraction, consistent with the notion of language acquisition as learning to process.

Second-language learners rarely arrive at native proficiency in a number of linguistic domains, i... more Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first-vs. second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in on-line language processing, we explore the hypothesis that children rely more heavily on multiword units in language learning than do adults learning a second language. To this end, we take an initial step towards using large-scale, corpus-based computational modeling as a tool for exploring the granularity of speakers' linguistic units. Employing a computational model of language learning, the Chunk-based Learner (CBL), we compare the usefulness of chunk-based knowledge in accounting for the speech of second-language learners vs. children and adults speaking their first language. Our findings suggest that while multiword units are likely to play a role in second-language learning, adults may learn less useful chunks, rely on them to a lesser extent, and arrive at them through different means than children learning a first language.

Are comprehension and production a single, integrated skill, or are they separate processes drawi... more Are comprehension and production a single, integrated skill, or are they separate processes drawing on a shared abstract knowledge of language? We argue that a fundamental constraint on memory, the Now-or-Never bottleneck, implies that language processing is incremental and that language learning occurs on-line. These properties are difficult to reconcile with the ‘abstract knowledge’ viewpoint, and crucially suggest that language comprehension and production are facets of a unitary skill. This viewpoint is exemplified in the Chunk-Based Learner, a computational acquisition model that processes incrementally and learns on-line. The model both parses and produces language; and implements the idea that language acquisition is nothing more than learning to process. We suggest that the Now-or-Never bottleneck also provides a strong motivation for unified perception-production models in other domains of communication and cognition.

Proceedings of the 37th Annual Conference of the Cognitive Science Society

There are considerable differences in language processing skill among the normal population. A k... more There are considerable differences in language processing
skill among the normal population. A key question for
cognitive science is whether these differences can be ascribed
to variations in domain-general cognitive abilities,
hypothesized to play a role in language, such as working
memory and statistical learning. In this paper, we present
experimental evidence pointing to a fundamental memory
skill—chunking—as an important predictor of cross-
individual variation in complex language processing.
Specifically, we demonstrate that chunking ability reflects
experience with language, as measured by a standard serial
recall task involving consonant combinations drawn from
naturally occurring text. Our results reveal considerable
individual differences in participants’ ability to use chunk
frequency information to facilitate sequence recall. Strikingly,
these differences predict variations across participants in the
on-line processing of complex sentences involving relative
clauses. Our study thus presents the first evidence tying the
fundamental ability for chunking to sentence processing skill,
providing empirical support for construction-based
approaches to language.

The Mental Lexicon

In recent years, psycholinguistic studies have built support for the notion that formulaic langua... more In recent years, psycholinguistic studies have built support for the notion that formulaic language is more widespread and pervasive in adult sentence processing than previously assumed. These findings are mirrored in a number of developmental studies, suggesting that children's item-
based units do not diminish, but persist into adulthood, in keeping with a number of approaches emerging from cognitive linguistics. In the present paper, we describe a simple, psychologically motivated computational model of language acquisition in which the learning and use of
formulaic expressions represents the foundation for comprehension and production processes. The model is shown to capture key psycholinguistic findings on children's sensitivity to the properties of multiword strings and use of lexically specific multiword frames in morphological development. The results of these simulations, we argue, stress the importance of adopting a developmental perspective to better understand how formulaic expressions come to play an important role in adult language use.

WIREs Cognitive Science, 5, 489-499, 2014

"The computational modeling of language development has enabled researchers to make impressive st... more "The computational modeling of language development has enabled researchers to make impressive strides towards achieving a comprehensive psychological account of the processes and mechanisms whereby children acquire their mother tongues. Nevertheless, the field's primary focus on distributional information has lead to little progress in elucidating the processes by which children learn to compute meanings beyond the level of single words. This lack of psychologically-motivated computational work on semantics poses an important challenge for usage-based computational accounts of acquisition in particular, which hold that grammatical development is closely tied to meaning. In the present review, we trace some initial steps towards answering this challenge through a survey of existing computational models of grammatical development that incorporate semantic information to learn to assign thematic roles and acquire argument structure. We argue that the time is ripe for usage-based computational accounts of grammatical development to move beyond purely distributional features of the input, and to incorporate information about the objects and actions observable in the learning environment. To conclude, we sketch possible avenues for extending previous approaches to modeling the role of semantics in grammatical development.
"

Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 2011

Whether the input available to children is sufficient to explain their ability to use language ha... more Whether the input available to children is sufficient to explain their ability to use language has been the subject of much theoretical debate in cognitive science. Here, we present a simple, developmentally motivated computational model that learns to comprehend and produce language when exposed to child-directed speech. The model uses backward transitional probabilities to create an inventory of ‘chunks’ consisting of one or more words. Language comprehension is approximated in terms of shallow parsing of adult speech and production as the reconstruction of the child’s actual utterances. The model functions in a fully incremental, on-line fashion, has broad cross-linguistic coverage, and is able to fit child data from Saffran’s (2002) statistical learning study. Moreover, word-based distributional information is found to be more useful than statistics over word classes. Together, these results suggest that much of children’s early linguistic behavior can be accounted for in a usage-based manner using distributional statistics.

In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society.

In line with usage-based accounts, recent psycholinguistic studies have confirmed that frequency... more In line with usage-based accounts, recent psycholinguistic
studies have confirmed that frequency of occurrence impacts
processing latencies for multiword strings (e.g., Arnon &
Snider, 2010). However, these studies have not been
concerned with the meaning of the multiword chunks in
question, which is central to accounts of formulaic language
rooted in cognitive linguistics (e.g., Wray, 2002). Here, we
address this issue by comparing processing latencies for three
types of multiword chunks: idiomatic expressions,
meaningful compositional phrases, and less meaningful
fragments. All three chunk types were matched for whole-
and sub-string frequency. Our results show that frequency
facilitates processing for all three chunk types, but to a lesser
extent than their “meaningfulness” (as assessed in a separate
norming study), indicating that the meanings of multiword
expressions may have implications for models of language
processing which extend beyond those of frequency of
occurrence.

Behavioral and Brain Sciences, 36, 366-367 (commentary on Pickering & Garrod).

While Pickering and Garrod argue convincingly for a unified system for language comprehension and... more While Pickering and Garrod argue convincingly for a unified system for language comprehension and production, they fail to explain how such a system might develop. Using a recent computational model of language acquisition as an example, we sketch a developmental perspective on the integration of comprehension and production. We conclude that only through development can we fully understand the intertwined nature of comprehension and production in adult processing.

Language and Speech, 2013

Previous research using picture/word matching tasks has demonstrated a tendency to incorrectly in... more Previous research using picture/word matching tasks has demonstrated a tendency to incorrectly interpret phrasally stressed strings as compounds. Using event-related potentials, we sought to determine whether this pattern stems from poor perceptual sensitivity to the compound/phrasal stress distinction, or from a post-perceptual bias in behavioral response selection. A secondary aim was to gain insight into the role played by contrastive stress patterns in online sentence comprehension. The behavioral results replicated previous findings of a preference for compounds, but the electrophysiological data suggested a robust sensitivity to both stress patterns. When incongruent with the context, both compound and phrasal stress elicited a sustained left-lateralized negativity. Moreover, incongruent compound stress elicited a centro-parietal negativity (N400), while incongruent phrasal stress elicited a late posterior positivity (P600). We conclude that the previous findings of a preference for compounds are due to response selection bias, and not a lack of perceptual sensitivity. The present results complement previous evidence for the immediate use of meter in semantic processing, as well as evidence for late interactions between prosodic and syntactic information.

Language 89 (4), 760-793

As children learn their mother tongues, they make systematic errors. For example, English-speakin... more As children learn their mother tongues, they make systematic errors. For example, English-speaking children regularly say “mouses” rather than “mice.” Because children’s errors aren’t explicitly corrected, it has been argued that children could never learn to make the transition to adult language based on the evidence available to them, and thus that learning even simple aspects of grammar is logically impossible without recourse to innate, language-specific constraints. Here, we examine the role children’s expectations play in language learning, and present a model of plural noun learning that generates a surprising prediction: at a given point in learning, exposure to regular plurals (e.g., rats) can decrease children’s tendency to over-regularize irregular plurals (e.g., mouses). Intriguingly, the model predicts that the same exposure should have the opposite effect earlier in learning. Consistent with this, we show that testing memory for items with regular plural labels contributes to a decrease in irregular plural over-regularization in six-year-olds, but an increase in four-year-olds. Our model and results suggest that children’s over-regularization errors both arise and resolve themselves as a consequence of the distribution of error in the linguistic environment, and that far from presenting a logical puzzle for learning, they are inevitable consequences of it.

Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2014

The flexibility and unbounded expressivity of our linguistic abilities is unparalleled in the bi... more The flexibility and unbounded expressivity of our linguistic
abilities is unparalleled in the biological world. Explaining
how children acquire this fundamental aspect of human
language is a key challenge for cognitive science. A recent
corpus study by Yang (2013) has cast doubt on the lexical
specificity of children’s productivity, as hypothesized by
usage-based approaches. Focusing on determiner-noun
combinations, he suggests that children possess an adult-like
determiner category. In this paper, we show that Yang’s
results may depend too heavily on an idealized notion of
frequency distributions. We propose that these issues may be
resolved by sidestepping sampling considerations and directly
modeling children’s actual language processing. We therefore
evaluate the abilities of two computational models to capture
children's productions of determiner-noun combinations. The
first model implements a probabilistic context-free grammar,
which acquires statistical information incrementally. A
second model, the Chunk-based Learner (CBL), provides a
simple instantiation of item-based learning. CBL outperforms
the rule-based model, successfully producing the vast
majority of the determiner-noun combinations in a dense
corpus of child speech. The results thus suggest that the case
against lexical specificity in children’s early determiner-noun
sequences may be overstated.

Words are often seen as the core representational units of language use, and the basic building b... more Words are often seen as the core representational units of language use, and the basic building blocks of language learning. Here, we provide novel empirical evidence for the role of multiword sequences in language learning by showing that, like words, multiword phrases show age-of-acquisition (AoA) effects. Words that are acquired earlier in childhood show processing advantages in adults on a variety of tasks. AoA effects highlight the role of words in the developing language system and illustrate the lasting impact of early-learned material on adult processing. Here, we show that such effects are not limited to single words: multiword phrases that are learned earlier in childhood are also easier to process in adulthood. In two reaction time studies, we show that adults respond faster to early-acquired phrases (categorized using corpus measures and subjective ratings) compared to later-acquired ones. The effect is not reducible to adult frequencies, plausibility, or lexical AoA. Like words, early-acquired phrases enjoy a privileged status in the adult language system. These findings further highlight the parallels between words and larger patterns, demonstrate the role of multiword units in learning, and provide novel support for models of language where units of varying sizes serve as building blocks for language

Developmental Science, 2021

Proceedings of the 41st Annual Conference of the Cognitive Science Society, 2019

Psychological Review, 2019

Proceedings of the 37th Annual Conference of the Cognitive Science Society

The Mental Lexicon

WIREs Cognitive Science, 5, 489-499, 2014

Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 2011

In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society.

Behavioral and Brain Sciences, 36, 366-367 (commentary on Pickering & Garrod).

Language and Speech, 2013

Language 89 (4), 760-793

Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2014