Global and Local Feature Distinctiveness Effects in Language Acquisition

Various aspects of semantic features drive early vocabulary development, but less is known about how the global and local structure of the overall semantic feature space influences language acquisition. A feature network of English words was constructed from a large database of adult feature production norms such that edges in the network represented feature distances between words (i.e., Manhattan distances of probability distributions of features elicited for each pair of words). A word's global feature distinctiveness is measured with respect to all other words in the network and a word's local feature distinctiveness is measured relative to words in sub-networks derived from clustering analyses. This paper investigates how feature distinctiveness of individual words at local and global scales of the network influences language acquisition. Regression analyses indicate that global feature distinctiveness was associated with earlier age of acquisition ratings, and was a stronger predictor of age of acquisition than local feature distinctiveness. These results suggest that the global structure of the semantic feature network could play an important role in language acquisition, whereby globally distinctive concepts help to structure vocabulary development over the lifespan.     

Topics in semantic representation

Processing language requires the retrieval of concepts from memory in response to an ongoing stream of information. This retrieval is facilitated if one can infer the gist of a sentence, conversation, or document and use that gist to predict related concepts and disambiguate words. This article analyzes the abstract computational problem underlying the extraction and use of gist, formulating this problem as a rational statistical inference. This leads to a novel approach to semantic representation in which word meanings are represented in terms of a set of probabilistic topics. The topic model performs well in predicting word association and the effects of semantic association and ambiguity on a variety of language-processing and memory tasks. It also provides a foundation for developing more richly structured statistical models of language, as the generative process assumed in the topic model can easily be extended to incorporate other kinds of semantic and syntactic structure.     

How do valence and meaning interact? The contribution of semantic control

The hub-and-spoke model of semantic cognition proposes that conceptual representations in a heteromodal ‘hub’ interact with and emerge from modality-specific features or ‘spokes’, including valence (whether a concept is positive or negative), along with visual and auditory features. As a result, valence congruency might facilitate our ability to link words conceptually. Semantic relatedness may similarly affect explicit judgements about valence. Moreover, conflict between meaning and valence may recruit semantic control processes. Here we tested these predictions using two-alternative forced-choice tasks, in which participants matched a probe word to one of two possible target words, based on either global meaning or valence. Experiment 1 examined timed responses in healthy young adults, while Experiment 2 examined decision accuracy in semantic aphasia patients with impaired controlled semantic retrieval following left hemisphere stroke. Across both experiments, semantically related targets facilitated valence matching, while related distractors impaired performance. Valence congruency was also found to facilitate semantic decision-making. People with semantic aphasia showed impaired valence matching and had particular difficulty when semantically related distractors were presented, suggesting that the selective retrieval of valence information relies on semantic control processes. Taken together, the results are consistent with the hypothesis that automatic access to the global meaning of written words affects the processing of valence, and that the valence of words is also retrieved even when this feature is task-irrelevant, affecting the efficiency of global semantic judgements.     

An efficient method for estimating semantic similarity based on feature overlap: Reliability and validity of semantic feature ratings

Two studies were conducted in which human participants rated pairs of words according to the perceived degree to which the words’ referents shared semantic features. The participants found the task intuitive, simple, and quick to complete. The ratings were reliable and valid. Interrater and interstudy correlations were high, and ratings were good predictors of known feature overlap values obtained from existing semantic feature norms.     

The effect of stress on the linguistic generalization of bilingual individuals

Spanish-English coordinate bilinguals were subjects in a GSR linguistic conditioning experiment using strong and mild buzzer conditions and spoken stimuli. Each subject was randomly assigned to one of two lists of words and one of two levels of buzzer sounds. A Spanish word from the Spanish list and an English word from the English list functioned as a conditioned word (CS). The lists were Spanish and English words related semantically and phonemically and unrelated to the CS. Generalization was studied under conscious and unconscious conditions. We found that both buzzer conditions resulted in significantly greater GSR responses to semantic and phonemic words than to words unrelated to the CS. Generalization to semantic words was not significantly greater than to phonemic words. There was a tendency toward greater phonemic than semantic generalization in the strong buzzer condition. The opposite was observed regarding the mild buzzer. The results were the same in both lists and languages. Under a conscious and unstressful condition, generalization to semantic words was found to be more prominent than to phonemic words. This suggests that under normal condition semantic generalization is mediated by conscious cognition. We concluded that strong emotion produces an increase in phonemic, as compared to semantic, generalization in both languages. Hence, primitivization of the subjects' cognitive and linguistic functioning is assumed to have occurred. These results are important in understanding the deleterious effect that stressful situations may have on linguistic functioning and cognition in bilinguals.     

Novel word integration in the mental lexicon: Evidence from unmasked and masked semantic priming

We sought to establish whether novel words can become integrated into existing semantic networks by teaching participants new meaningful words and then using these new words as primes in two semantic priming experiments, in which participants carried out a lexical decision task to familiar words. Importantly, at no point in training did the novel words co-occur with the familiar words that served as targets in the primed lexical decision task, allowing us to evaluate semantic priming in the absence of direct association. We found that familiar words were primed by the newly related novel words, both when the novel word prime was unmasked (Experiment 1) and when it was masked (Experiment 2), suggesting that the new words had been integrated into semantic memory. Furthermore, this integration was strongest after a 1-week delay and was independent of explicit recall of the novel word meanings: Forgetting of meanings did not attenuate priming. We argue that even after brief training, newly learned words become an integrated part of the adult mental lexicon rather than being episodically represented separately from the lexicon.     

Transfer of learning in avoiding false memory: The roles of warning,immediate feedback,and incentive

Participants learned semantic associates and were tested in the Deese–Roediger–McDermott (DRM) paradigm. A multiple-trial learning procedure with warning, feedback, and monetary incentive was employed to reduce false memory. Results showed that there was a progressive reduction of false memory over the trials as well as a generalization of learning to new lists of words in avoiding the critical nonpresented words attributable to explicit warning, feedback, and incentive, respectively. Both the feedback and the monetary incentive had an effect beyond what an explicit warning could obtain. In addition, participants were found to achieve false-memory reduction by enhancing the activation of the critical words and the monitoring process, rather than by strengthening the verbatim processing of the list words. It was concluded that false memory may not be as impervious to correction as was believed insofar as an effective training method is applied.     

Transfer of learning in avoiding false memory: the roles of warning, immediate feedback, and incentive

Participants learned semantic associates and were tested in the Deese-Roediger-McDermott (DRM) paradigm. A multiple-trial learning procedure with warning, feedback, and monetary incentive was employed to reduce false memory. Results showed that there was a progressive reduction of false memory over the trials as well as a generalization of learning to new lists of words in avoiding the critical nonpresented words attributable to explicit warning, feedback, and incentive, respectively. Both the feedback and the monetary incentive had an effect beyond what an explicit warning could obtain. In addition, participants were found to achieve false-memory reduction by enhancing the activation of the critical words and the monitoring process, rather than by strengthening the verbatim processing of the list words. It was concluded that false memory may not be as impervious to correction as was believed insofar as an effective training method is applied.     

Semantic feature production norms for a large set of objects and events

Semantic features produced by speakers of a language when given a word corresponding to a concept have provided insight into numerous behavioral phenomena concerning semantic representation in language-impaired and -unimpaired speakers. A number of theories concerning the organization of semantic memory have used features as their starting point. Here, we provide a set of feature norms collected from approximately 280 participants for a total of 456 words (169 nouns referring to objects, 71 nouns referring to events, and 216 verbs referring to events). Whereas a number of feature norms for object concepts already exist, we provide the first set of norms for event concepts. We have used these norms (for both objects and events) in research addressing questions concerning the similarities and differences between the semantic representation of objects and events and in research concerning the interface between semantics and syntax, given that events can be expressed in language as nouns or verbs. Some of this research is summarized here. These norms may be downloaded from www.psychonomic.org/archive.     

Statistical learning using real-world scenes: extracting categorical regularities without conscious intent

ABSTRACT— Recent work has shown that observers can parse streams of syllables, tones, or visual shapes and learn statistical regularities in them without conscious intent (e.g., learn that A is always followed by B). Here, we demonstrate that these statistical-learning mechanisms can operate at an abstract, conceptual level. In Experiments 1 and 2, observers incidentally learned which semantic categories of natural scenes covaried (e.g., kitchen scenes were always followed by forest scenes). In Experiments 3 and 4, category learning with images of scenes transferred to words that represented the categories. In each experiment, the category of the scenes was irrelevant to the task. Together, these results suggest that statistical-learning mechanisms can operate at a categorical level, enabling generalization of learned regularities using existing conceptual knowledge. Such mechanisms may guide learning in domains as disparate as the acquisition of causal knowledge and the development of cognitive maps from environmental exploration.     

Checking and bootstrapping lexical norms by means of word similarity indexes

In psychology, lexical norms related to the semantic properties of words, such as concreteness and valence, are important research resources. Collecting such norms by asking judges to rate the words is very time consuming, which strongly limits the number of words that compose them. In the present article, we present a technique for estimating lexical norms based on the latent semantic analysis of a corpus. The analyses conducted emphasize the technique??s effectiveness for several semantic dimensions. In addition to the extension of norms, this technique can be used to check human ratings to identify words for which the rating is very different from the corpus-based estimate.     

语义表征具身理论:情绪在概念表征中的作用

概念如何被表征是认知科学的热点问题,其中抽象概念如何表征是当前具身认知最具争议性的话题之一。与前期概念隐喻理论(强调意象图式)和知觉符号理论(强调情境内省信息)的观点不同,语义表征具身理论强调情绪经验信息在抽象概念表征和加工中的作用。具体而言,具体概念的表征主要来自感觉运动信息,而抽象概念的表征主要来自情绪经验信息和语言信息。研究证明,抽象概念的高情绪经验信息能够促进词汇的加工,且这一促进作用受词汇情绪效价的调节。未来研究应进一步考虑影响情绪经验信息发挥作用的因素,比如语言信息的丰富性、情绪唤醒或个体的情绪状态等。     

Longitudinal Analysis of Early Semantic Networks: Preferential Attachment or Preferential Acquisition?

ABSTRACT— Analyses of adult semantic networks suggest a learning mechanism involving preferential attachment: A word is more likely to enter the lexicon the more connected the known words to which it is related. We introduce and test two alternative growth principles: preferential acquisition—words enter the lexicon not because they are related to well-connected words, but because they connect well to other words in the learning environment—and the lure of the associates—new words are favored in proportion to their connections with known words. We tested these alternative principles using longitudinal analyses of developing networks of 130 nouns children learn prior to the age of 30 months. We tested both networks with links between words represented by features and networks with links represented by associations. The feature networks did not predict age of acquisition using any growth model. The associative networks grew by preferential acquisition, with the best model incorporating word frequency, number of phonological neighbors, and connectedness of the new word to words in the learning environment, as operationalized by connectedness to words typically acquired by the age of 30 months.     

Perception: The interface between cognition and the external world

In contrast to researchers who emphasize the distinction between perception and cognition it is claimed that the perceptual system is closely intertwined with cognition and with our comprehension of the external world. This claim is supported by evidence for two characteristic features of human information processing. One of these features is the use of mental models. If mental models are assumed to be anchored in the perceptual system it will not be necessary to assume a "little man in the head" who reads off the model. Moreover, perceptually based mental models will provide a referential semantics by anchoring mentally represented concepts in the external world. The other feature is the use of perceptually based perspectives in cognition, such as actor or observer perspectives in social cognition. It is concluded that human beings consistently interact within the real world--also when they are just thinking--and that this becomes possible via perceptual processes.     

纳西象形文字识别中的形、音、义激活

对纳西象形文字识别中的形、音、义激活进行了考察。实验1采用色词干扰的实验范式。结果表明,纳西象形文字的字形比字音和语义更易被激活。命名颜色字的形似字的颜色比命名颜色字的音同或音似字、语义联想字的颜色快。实验2采用色词干扰实验范式的变式。结果表明,当SOA=100ms时,颜色字及其形似字对颜色块命名的启动效应显著。当SOA为200ms和400ms时,颜色字的语义联想字对颜色块命名的启动效应显著。整个研究表明,在纳西象形文字识别中,字形信息首先被激活,其次是语义,字音的激活不明显。纳西象形文字的识别符合直通假设。所以如此,与纳西象形文字的特点有关     

Bayesian analogy with relational transformations

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought.     

Instantiated features and the use of "rules."

Classification "rules" in expert and everyday discourse are usually deficient by formal standards, lacking explicit decision procedures and precise terms. The authors argue that a central function of such weak rules is to focus on perceptual learning rather than to provide definitions. In 5 experiments, transfer following learning of family resemblance categories was influenced more by familiar-appearing features than by novel-appearing features equally acceptable under the rule. This occurred both when rules were induced and when rules were given at the beginning of instruction. To model this and other phenomena in categorization, features must be represented on 2 levels: informational and instantiated. These 2 feature levels are crucial to provide broad generalization while reflecting the known peculiarities of a complex world.     

The different representational frameworks underpinning abstract and concrete knowledge: Evidence from odd-one-out judgements

Recent evidence from neuropsychological investigations of individuals with global aphasia and deep or deep-phonological dyslexia suggests that abstract and concrete concepts are underpinned by qualitatively different representational frameworks. Abstract words are represented primarily by their association to other words, whilst concrete words are represented primarily by their taxonomic similarity to one another. In the current study, we present the first evidence for this association/similarity distinction to be gathered from healthy research participants. Using a semantic odd-one-out task, it is shown that normal participants identify associative connections more quickly than similarity-based connections when processing abstract words, but that the pattern is reversed for concrete words. It is also demonstrated that the typical concrete-word advantage observed in many cognitive tasks is abolished and even reversed when participants have to comprehend the semantic associations between words. The data provide converging evidence for the different representational frameworks hypothesis and suggest that claims based on information from previous neuropsychological investigations can be generalized to normal cognition.     

Age-of-acquisition,imagery, familiarity and meaningfulness norms for 543 words

The age at which words are first learned appears to be more influential in determining the ease of retrieving words from semantic memory than objective frequency, familiarity, imagery, and meaningfulness. To facilitate research on a wider variety of tasks, we present norms for 543 words for age-of-acquisition, imagery, familiarity, and meaningfulness. Most of the words form single-solution anagrams. There are 471 six-letter nouns and 72 five-letter words. Also reported are the means, SDs, and ranges for each dimension and the intercorrelations between dimensions. Intergroup reliabilities ranged from .847 to .982.     

Interpreting semantic clustering effects in free recall

The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organised, and retrieved. One pervasive finding is that when a pair of semantically related words (e.g., "cat" and "dog") is embedded in the studied list, the related words are often recalled successively. This tendency to successively recall semantically related words is termed semantic clustering (Bousfield, 1953; Bousfield & Sedgewick, 1944; Cofer, Bruce, & Reicher, 1966). Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. However, it is often difficult to gain insights into individual participants' internal semantic models, and for this reason researchers typically rely on standardised semantic similarity metrics. Here we use simulations to gain insights into the expected magnitudes of semantic clustering effects given systematic differences between participants' internal similarity models and the similarity metric used to quantify the degree of semantic clustering. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.