Verbal statistical learning: Prior knowledge impacts word identification but not metacognition

It is well-known that individuals can identify novel words in a stream of an artificial language using statistical dependencies. While underlying computations are thought to be similar from one stream to another (e.g. transitional probabilities between syllables), performance are not similar. According to the “linguistic entrenchment” hypothesis, this would be due to the fact that individuals have some prior knowledge regarding co-occurrences of elements in speech which intervene during verbal statistical learning. The focus of previous studies was on task performance. The goal of the current study is to examine the extent to which prior knowledge impacts metacognition (i.e. ability to evaluate one’s own cognitive processes). Participants were exposed to two different artificial languages. Using a fully Bayesian approach, we estimated an unbiased measure of metacognitive efficiency and compared the two languages in terms of task performance and metacognition. While task performance was higher in one of the languages, the metacognitive efficiency was similar in both languages. In addition, a model assuming no correlation between the two languages better accounted for our results compared to a model where correlations were introduced. We discuss the implications of our findings regarding the computations which underlie the interaction between input and prior knowledge during verbal statistical learning.

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How well does Statistical Learning Address the Challenges of Real-World Language Learning?

The Oxford Handbook of Psycholinguistics ◽

10.1093/oxfordhb/9780198786825.013.30 ◽

2018 ◽

pp. 689-713

Author(s):

Lucia Sweeney ◽

Rebecca L. Gómez

Keyword(s):

Individual Differences ◽

Natural Language ◽

Language Learning ◽

Statistical Learning ◽

Cognitive Processes ◽

Real World ◽

Learning Ability ◽

World Language ◽

Word Forms ◽

Transitional Probabilities

How well does statistical learning address the challenges of real-world language learning? This chapter presents progress in the domain of statistical learning since Saffran et al. (1996) conducted their seminal work. It highlights the extension of statistical learning to acquisition of natural language, and reviews investigations of how infants and adults segment words from speech, acquire word forms, and form abstract grammatical categories through tracking of transitional probabilities and non-adjacent dependencies. It also focuses on research demonstrating the influence of individual differences on statistical learning ability along with neuroimaging studies that reveal cognitive processes supporting statistical learning. The chapter ends by suggesting avenues of research that would further extend the application of statistical learning to natural language acquisition.

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Top-Down Structure Influences Learning of Non-Adjacent Dependencies in an Artificial Language

10.31234/osf.io/uw5nx ◽

2017 ◽

Author(s):

Felix Hao Wang ◽

Jason D Zevin ◽

Toben Herbert Mintz

Keyword(s):

Statistical Learning ◽

Language Learners ◽

American Psychological Association ◽

Hierarchical Organization ◽

Artificial Language ◽

American Psychological ◽

Natural Languages ◽

Artificial Languages ◽

The Subject ◽

Minimal Sequences

Due to the hierarchical organization of natural languages, words that are syntactically related are not always linearly adjacent. For example, the subject and verb in the child always runs agree in person and number, although they are not adjacent in the sequences of words. Since such dependencies are indicative of abstact linguistc structure, it is of significant theoretical interest how these relationships are acquired by language learners. Most experiments that investigate non-adjacent dependency (NAD) learning have used artificial languages in which the to-be-learned dependencies are isolated, by presenting the minimal sequences that contain the dependent elements. However, dependencies in natural language are not typically isolated in this way. We report the first demonstration to our knowledge of successful learning of embedded NADs, in which silences do not mark dependency boundaries. Subjects heard passages of English with a predictable structure, interspersed with passages of the artificial language. The English sentences were designed to induce boundaries in the artificial languages. In Experiment 1 & 3 the artificial NADs were contained within the induced boundaries and subjects learned them, whereas in Experiment 2 & 4, the NADs crossed the induced boundaries and subjects did not learn them. We take this as evidence that sentential structure was “carried over” from the English sentences and used to organize the artificial language. This approach provides several new insights into the basic mechanisms of NAD learning in particular and statistical learning in general. © American Psychological Association. This paper is not the copy of record and may not exactly replicate the final, authoritative version of the article. Please do not copy or cite without authors permission. The final article is available via its DOI: 10.1037/xge0000384

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Principles of compiling artificial languages

SCIENTIFIC WORK ◽

10.36719/2663-4619/56/40-46 ◽

2020 ◽

Vol 56 (07) ◽

pp. 40-46

Author(s):

Khayala Mugamat Mursaliyeva ◽

Keyword(s):

Natural Language ◽

Modern World ◽

Linguistic Landscape ◽

Artificial Language ◽

Natural Consequence ◽

Modern Language ◽

Artificial Languages ◽

The World ◽

The Creation

The explosion of information and the ever-increasing number of international languages make the modern language situation very difficult. The interaction of languages ultimately leads to the creation of international artificial languages that operate in parallel with the world`s languages. The expansion of interlinguistic issues is a natural consequence of the aggravation of the linguistic landscape of the modern world. The modern interlinguistic dialect, which is defined as a field of linguistics that studies international languages and international languages as a means of communication, deals with the importance of overcoming the barrier.The problem of international artificial languages is widely covered in the writings of I.A.Baudouin de Courtenay, V.P.Qrigorev, N.L.Gudskov, E.K.Drezen, A.D.Dulchenko, M.I.Isayev, S.N.Kuznechov, A.D.Melnikov and many other scientists. Key words:the concept of natural language, the concept of artificial language, the degree of artificiality of language, the authenticity of language

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Priors and Prejudice: How prior knowledge shapes intergroup perception

10.31234/osf.io/3tyrg ◽

2021 ◽

Author(s):

Hugh McGovern ◽

Marte Otten

Keyword(s):

Social Psychology ◽

Prior Knowledge ◽

Cognitive Processes ◽

Social Neuroscience ◽

Intergroup Bias ◽

Predictive Processing ◽

Future Research ◽

Intergroup Perception ◽

The Brain ◽

Processing Framework

Bayesian processing has become a popular framework by which to understand cognitive processes. However, relatively little has been done to understand how Bayesian processing in the brain can be applied to understanding intergroup cognition. We assess how categorization and evaluation processes unfold based on priors about the ethnic outgroup being perceived. We then consider how the precision of prior knowledge about groups differentially influence perception depending on how the information about that group was learned affects the way in which it is recalled. Finally, we evaluate the mechanisms of how humans learn information about other ethnic groups and assess how the method of learning influences future intergroup perception. We suggest that a predictive processing framework for assessing prejudice could help accounting for seemingly disparate findings on intergroup bias from social neuroscience, social psychology, and evolutionary psychology. Such an integration has important implications for future research on prejudice at the interpersonal, intergroup, and societal levels.

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Auditory word recognition across the lifespan

Linguistic Approaches to Bilingualism ◽

10.1075/lab.14030.blu ◽

2016 ◽

Vol 6 (1-2) ◽

pp. 119-146 ◽

Cited By ~ 12

Author(s):

Henrike K. Blumenfeld ◽

Scott R. Schroeder ◽

Susan C. Bobb ◽

Max R. Freeman ◽

Viorica Marian

Keyword(s):

Older Adults ◽

Cognitive Control ◽

Cognitive Processes ◽

Processing Speed ◽

Word Identification ◽

Age Related ◽

Auditory Word ◽

Auditory Word Recognition ◽

The Relationship ◽

Age Related Changes

Abstract Recent research suggests that bilingual experience reconfigures linguistic and nonlinguistic cognitive processes. We examined the relationship between linguistic competition resolution and nonlinguistic cognitive control in younger and older adults who were either bilingual or monolingual. Participants heard words in English and identified the referent among four pictures while eye-movements were recorded. Target pictures (e.g., cab) appeared with a phonological competitor picture (e.g., cat) and two filler pictures. After each eye-tracking trial, priming probes assessed residual activation and inhibition of target and competitor words. When accounting for processing speed, results revealed that age-related changes in activation and inhibition are smaller in bilinguals than in monolinguals. Moreover, younger and older bilinguals, but not monolinguals, recruited similar inhibition mechanisms during word identification and during a nonlinguistic Stroop task. Results suggest that, during lexical access, bilinguals show more consistent competition resolution and recruitment of cognitive control across the lifespan than monolinguals.

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A fully Bayesian approach to assessment of model adequacy in inverse problems

Statistical Methodology ◽

10.1016/j.stamet.2012.10.005 ◽

2013 ◽

Vol 12 ◽

pp. 71-83 ◽

Cited By ~ 2

Author(s):

Sourabh Bhattacharya

Keyword(s):

Inverse Problems ◽

Bayesian Approach ◽

Model Adequacy ◽

Fully Bayesian

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Unraveling What’s on Our Minds

10.1093/oxfordhb/9780190464745.013.29 ◽

2018 ◽

Author(s):

Claire M. Zedelius ◽

Jonathan W. Schooler

Keyword(s):

Decision Making ◽

Working Memory ◽

Task Performance ◽

Cognitive Processes ◽

Positive Mood ◽

Mind Wandering ◽

Different Types ◽

And Behavior

Mind-wandering encompasses a variety of different types of thought, involving various different experiential qualities, emotions, and cognitive processes. Much is lost by simply lumping them together, as is typically done in the literature. The goal of this chapter is to explore the nuances that distinguish different types of mind-wandering. The chapter draws on research on mind-wandering as well as other literatures to gain a better understanding of how these different types of mind-wandering affect cognition and behavior. It specifically discusses the distinct effects of different types of mind-wandering on task performance, working memory, mood, and creativity. Finally, the chapter discusses the idea of deliberate engagement in particular types of mind-wandering as a way to achieve desirable outcomes, such as maintaining a positive mood, enhancing creativity, or aiding decision-making.

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Statistical Properties in Jazz Improvisation Underline Individuality of Musical Representation

NeuroSci ◽

10.3390/neurosci1010004 ◽

2020 ◽

Vol 1 (1) ◽

pp. 24-43

Author(s):

Tatsuya Daikoku

Keyword(s):

Statistical Learning ◽

Time Course ◽

Statistical Properties ◽

Transitional Probability ◽

Jazz Improvisation ◽

Statistical Knowledge ◽

Future State ◽

Structured Information ◽

Transitional Probabilities ◽

The Brain

Statistical learning is an innate function in the brain and considered to be essential for producing and comprehending structured information such as music. Within the framework of statistical learning the brain has an ability to calculate the transitional probabilities of sequences such as speech and music, and to predict a future state using learned statistics. This paper computationally examines whether and how statistical learning and knowledge partially contributes to musical representation in jazz improvisation. The results represent the time-course variations in a musician’s statistical knowledge. Furthermore, the findings show that improvisational musical representation might be susceptible to higher- but not lower-order statistical knowledge (i.e., knowledge of higher-order transitional probability). The evidence also demonstrates the individuality of improvisation for each improviser, which in part depends on statistical knowledge. Thus, this study suggests that statistical properties in jazz improvisation underline individuality of musical representation.

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