78,179 research outputs found
Computational and Robotic Models of Early Language Development: A Review
We review computational and robotics models of early language learning and
development. We first explain why and how these models are used to understand
better how children learn language. We argue that they provide concrete
theories of language learning as a complex dynamic system, complementing
traditional methods in psychology and linguistics. We review different modeling
formalisms, grounded in techniques from machine learning and artificial
intelligence such as Bayesian and neural network approaches. We then discuss
their role in understanding several key mechanisms of language development:
cross-situational statistical learning, embodiment, situated social
interaction, intrinsically motivated learning, and cultural evolution. We
conclude by discussing future challenges for research, including modeling of
large-scale empirical data about language acquisition in real-world
environments.
Keywords: Early language learning, Computational and robotic models, machine
learning, development, embodiment, social interaction, intrinsic motivation,
self-organization, dynamical systems, complexity.Comment: to appear in International Handbook on Language Development, ed. J.
Horst and J. von Koss Torkildsen, Routledg
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Ambiguity is a double-edged sword: similarity references in communication
Designers often explain new concepts and new ideas by reference to existing designs. This is parsimonious, as it only requires a pointer to the referent and a description of the modifications. Such descriptions can be extremely powerful, expressing the entire context of a design or a process in a few words. However similarity assertions are inherently ambiguous, because they depend not only on the chosen description but also on the intention behind the similarity comparison. In this paper we attempt to analyse the effect that the ambiguity of similarity references has on communication and idea generation in design. The reinterpretation of a similarity assertion can be extremely creative, where ambiguity allows for new interpretations of a problem. At the same time, it can make accurate communication extremely difficult because every assertion can be interpreted differently unless the context is fully shared
Children’s Early Awareness of Comprehension as Evident in Their Spontaneous Corrections of Speech Errors
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147836/1/cdev12862_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147836/2/cdev12862.pd
The role of Comprehension in Requirements and Implications for Use Case Descriptions
Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements.
Therefore, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Hence, the paper examines guidelines which have been proposed, in this case for use case descriptions, and the extent to which they agree with discourse process theory; before suggesting refinements to the guidelines which attempt to utilise lessons learned from our richer understanding of the underlying discourse process theory. For example, we suggest subtly different sets of writing guidelines for the different tasks of requirements, specification and design
Prince Charming has Perfect White Teeth: Performativity and Media Education
This paper argues that Judith Butler’s post structuralist theory of performativity provides a valuable tool for understanding how students might contest prevailing hegemonic gender discourses in media education classrooms. It suggests an alternative to structuralist "empowerment" and "critical pedagogy" approaches, which continue to motivate many media educators, despite serious questions being asked about their effectiveness. The paper draws on data collected from a unit of work about video games, completed by year ten students at an all boys’ secondary school in Brisbane. It argues that many media related activities fail to elicit genuinely "critical" responses because they are complicit in the regulation of hegemonic discourses. It suggests that teachers are more likely to create the potential for variation in their students’ gender performances if activities are dialogic and open-ended and avoid placing emphasis on discourses of excellence and competition
Comprehension, Use Cases and Requirements
Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements.
In contrast, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Furthermore, that these assumptions may lead to rules which detract from the quality of the requirements document and, thus, the understanding gained by the reader. Finally the paper suggests lessons learned which may be useful in formulating future guidance for the production of requirements documentation
Goldilocks Forgetting in Cross-Situational Learning
Given that there is referential uncertainty (noise) when learning words, to what extent can forgetting filter some of that noise out, and be an aid to learning? Using a Cross Situational Learning model we find a U-shaped function of errors indicative of a "Goldilocks" zone of forgetting: an optimum store-loss ratio that is neither too aggressive nor too weak, but just the right amount to produce better learning outcomes. Forgetting acts as a high-pass filter that actively deletes (part of) the referential ambiguity noise, retains intended referents, and effectively amplifies the signal. The model achieves this performance without incorporating any specific cognitive biases of the type proposed in the constraints and principles account, and without any prescribed developmental changes in the underlying learning mechanism. Instead we interpret the model performance as more of a by-product of exposure to input, where the associative strengths in the lexicon grow as a function of linguistic experience in combination with memory limitations. The result adds a mechanistic explanation for the experimental evidence on spaced learning and, more generally, advocates integrating domain-general aspects of cognition, such as memory, into the language acquisition process
Robust Processing of Natural Language
Previous approaches to robustness in natural language processing usually
treat deviant input by relaxing grammatical constraints whenever a successful
analysis cannot be provided by ``normal'' means. This schema implies, that
error detection always comes prior to error handling, a behaviour which hardly
can compete with its human model, where many erroneous situations are treated
without even noticing them.
The paper analyses the necessary preconditions for achieving a higher degree
of robustness in natural language processing and suggests a quite different
approach based on a procedure for structural disambiguation. It not only offers
the possibility to cope with robustness issues in a more natural way but
eventually might be suited to accommodate quite different aspects of robust
behaviour within a single framework.Comment: 16 pages, LaTeX, uses pstricks.sty, pstricks.tex, pstricks.pro,
pst-node.sty, pst-node.tex, pst-node.pro. To appear in: Proc. KI-95, 19th
German Conference on Artificial Intelligence, Bielefeld (Germany), Lecture
Notes in Computer Science, Springer 199
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