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If human language must be squeezed through a narrow cognitive bottleneck, what are the implications for language processing, acquisition, change, and structure? In our target article, we suggested that the implications are far-reaching and form the basis of an integrated account of many apparently unconnected aspects of language and language processing, as well as suggesting revision of many existing theoretical accounts. With some exceptions, commentators were generally supportive both of the existence of the bottleneck and its potential implications. Many commentators (...) No categories |
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Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning (...) |
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In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab‐based experiments, using artificial languages, many of the cues and features that are part of real‐world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language‐like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in (...) |
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Infant language learners are faced with the difficult inductive problem of determining how new words map to novel or known objects in their environment. Bayesian inference models have been successful at using the sparse information available in natural child-directed speech to build candidate lexicons and infer speakers’ referential intentions. We begin by asking how a Bayesian model optimized for monolingual input generalizes to new monolingual or bilingual corpora and find that, especially in the case of the bilingual input, the model (...) |
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Cross-situational word learning, like any statistical learning problem, involves tracking the regularities in the environment. However, the information that learners pick up from these regularities is dependent on their learning mechanism. This article investigates the role of one type of mechanism in statistical word learning: competition. Competitive mechanisms would allow learners to find the signal in noisy input and would help to explain the speed with which learners succeed in statistical learning tasks. Because cross-situational word learning provides information at multiple (...) No categories |
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Yang returns to the problem of referential ambiguity, addressed in the opening paper by Gleitman and Trueswell. Using a computational approach, he argues that “big data” approaches to resolving referential ambiguity are destined to fail, because of the inevitable computational explosion needed to keep track of contextual associations present when a word is uttered. Yang tests several computational models, two of which depend on one‐trial learning, as described in Gleitman and Trueswell’s paper. He concludes that such models outperform cross‐situational learning (...) |
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Cognitive Science, Volume 46, Issue 4, April 2022. |
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Variability is prevalent in early language acquisition, but, whether it supports or hinders learning is unclear; while target variability has been shown to facilitate word learning, variability in competitor items has been shown to make the task harder. Here, we tested whether background variability could boost learning in a referent selection task. Two groups of 2-year-old children saw arrays of one novel and two known objects on a screen, and they heard a novel or known label. Stimuli were identical across (...) |
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It is well-established that toddlers can correctly select a novel referent from an ambiguous array in response to a novel label. There is also a growing consensus that robust word learning requires repeated label-object encounters. However, the effect of the context in which a novel object is encountered is less well-understood. We present two embodied neural network replications of recent empirical tasks, which demonstrated that the context in which a target object is encountered is fundamental to referent selection and word (...) No categories |
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Theories of cognitive development must address both the issue of how children bring their knowledge to bear on behavior in-the-moment, and how knowledge changes over time. We argue that seeking answers to these questions requires an appreciation of the dynamic nature of the developing system in its full, reciprocal complexity. We illustrate this dynamic complexity with results from two lines of research on early word learning. The first demonstrates how the child's active engagement with objects and people supports referent selection (...) |
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Theories of cognitive development must address both the issue of how children bring their knowledge to bear on behavior in‐the‐moment, and how knowledge changes over time. We argue that seeking answers to these questions requires an appreciation of the dynamic nature of the developing system in its full, reciprocal complexity. We illustrate this dynamic complexity with results from two lines of research on early word learning. The first demonstrates how the child's active engagement with objects and people supports referent selection (...) No categories |
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This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary (...) |
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Across a series of four experiments with 3- to 4-year-olds we demonstrate how cognitive mechanisms supporting noun learning extend to the mapping of actions to objects. In Experiment 1 the demonstration of a novel action led children to select a novel, rather than a familiar object. In Experiment 2 children exhibited long-term retention of novel action-object mappings and extended these actions to other category members. In Experiment 3 we showed that children formed an accurate sensorimotor record of the novel action. (...) No categories |
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One cue that may facilitate children's word learning is iconicity, or the correspondence between a word's form and meaning. Some have even proposed that iconicity in the early lexicon may serve to help children learn how to learn words, supporting the acquisition of even noniconic, or arbitrary, word–referent associations. However, this proposal remains untested. Here, we investigate the iconicity of caregivers’ speech to young children during a naturalistic free‐play session with novel stimuli and ask whether the iconicity of caregivers’ speech (...) |
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When a toddler knows a word, what does she actually know? Many categories have multiple relevant properties; for example, shape and color are relevant to membership in the category banana. How do toddlers prioritize these properties when recognizing familiar words, and are there systematic differences among children? In this study, toddlers viewed pairs of objects associated with prototypical colors. On some trials, objects were typically colored ; on other trials, colors were switched. On each trial, toddlers were directed to find (...) |
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This article introduces the Special Issue and its focus on research in language evolution with emphasis on theory as well as computational and robotic modeling. A key theme is based on the growth of evolutionary developmental biology or evo-devo. The Special Issue consists of 13 articles organized in two sections: A) Theoretical foundations and B) Modeling and simulation studies. All the papers are interdisciplinary in nature, encompassing work in biological and linguistic foundations for the study of language evolution as well (...) |
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One of the great challenges in word learning is that words are typically uttered in a context with many potential referents. Children's tendency to associate novel words with novel referents, which is taken to reflect a mutual exclusivity (ME) bias, forms a useful disambiguation mechanism. We study semantic learning in pragmatic agents—combining the Rational Speech Act model with gradient‐based learning—and explore the conditions under which such agents show an ME bias. This approach provides a framework for investigating a pragmatic account (...) |
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There is substantial variation in language experience, yet there is surprising similarity in the language structure acquired. Constraints on language structure may be external modulators that result in this canalization of language structure, or else they may derive from the broader, communicative environment in which language is acquired. In this paper, the latter perspective is tested for its adequacy in explaining robustness of language learning to environmental variation. A computational model of word learning from cross-situational, multimodal information was constructed and (...) |
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Evolutionary developmental systems theory stresses that selection pressures operate on entire developmental systems rather than just genes. This study extends this approach to language evolution, arguing that selection pressure may operate on two quasi-independent timescales. First, children clearly must acquire language successfully and evolution must equip them with the tools to do so. Second, while this is developing, they must also communicate with others in the moment using partially developed knowledge. These pressures may require different solutions, and their combination may (...) |
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Many animals can be trained to perform novel tasks. People, too, can be trained, but sometime in early childhood people transition from being trainable to something qualitatively more powerful—being programmable. We argue that such programmability constitutes a leap in the way that organisms learn, interact, and transmit knowledge, and that what facilitates or enables this programmability is the learning and use of language. We then examine how language programs the mind and argue that it does so through the manipulation of (...) |
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Many animals can be trained to perform novel tasks. People, too, can be trained, but sometime in early childhood people transition from being trainable to something qualitatively more powerful—being programmable. We argue that such programmability constitutes a leap in the way that organisms learn, interact, and transmit knowledge, and that what facilitates or enables this programmability is the learning and use of language. We then examine how language programs the mind and argue that it does so through the manipulation of (...) |
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