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Australian State/Territory : VIC
Research Topic : Speech
Field of Research : Cognitive Science
Status : Closed
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Cognitive Science (5)
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  • Researchers (10)
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  • Funded Activity

    Discovery Projects - Grant ID: DP120100883

    Funder
    Australian Research Council
    Funding Amount
    $127,500.00
    Summary
    A computational and experimental investigation into the organisation of letters in reading. In alphabetical languages, people need to learn to organise individual letters into groups so that they can read efficiently. This project will develop a model of this process, which will allow great insight into this key aspect of reading in terms of what the most efficient way of doing this is and what may go wrong and cause reading problems.
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    Funded Activity

    Discovery Projects - Grant ID: DP170101857

    Funder
    Australian Research Council
    Funding Amount
    $150,000.00
    Summary
    Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The .... Using large scale modelling to understand reading development and dyslexia. This project aims to construct a computational model of reading that makes quantitative predictions about reading behaviour and dyslexia. It will test theories of reading development and dyslexia based on what they predict in terms of reading performance, predictions which many theories of dyslexia do not make. The model will be in English, French and Italian, which offer rich and constraining data to test the model. The project is expected to explain the link between reading performance and underlying influences and why dyslexia manifests differently in different languages.
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    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0347079

    Funder
    Australian Research Council
    Funding Amount
    $160,000.00
    Summary
    Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufact .... Surface and strain measurement facilities for the investigation of intelligent CAD approaches. The basis of machine learning approaches is the ability to learn or train a system from data gathered through experiments or experience. A major short coming in the development and application of such methods is the lack of good quantitative data. Here we propose the acquisition of dimensional and strain measurement facilities that will allow the investigation of such methods in the context of manufacturing - in particular sheet metal components for the automotive industry. The facilities will enable a database of dimensional and strain information to be established in support of related manufacturing R&D projects.
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    Funded Activity

    Discovery Projects - Grant ID: DP150103280

    Funder
    Australian Research Council
    Funding Amount
    $301,300.00
    Summary
    Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the po .... Learning from others: Inductive reasoning based on human-generated data. Most of the data we see every day, from politics to gossip, comes from other people. Making inferences about such data is difficult because the people who provided it may have biases or limitations in their knowledge that we do not know about and must figure out. This project uses a series of experiments tied to normative computational models of social reasoning to explore how people solve this problem. This work has the potential to make a major impact in understanding how information is understood and shared, especially when it is about topics that people lack firsthand knowledge about, like climate change. The computational models also have applications to the development of expert systems upon which our information economy relies.
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    Funded Activity

    Special Research Initiatives - Grant ID: SR0354513

    Funder
    Australian Research Council
    Funding Amount
    $20,000.00
    Summary
    The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, ex .... The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, explore new ways in which computational models inform our understanding of human languages, and exploit new opportunities for applying theories of language in the development of human language technologies.
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