ARC Communications Research Network. Building on a strong platform of existing research excellence, the Aim of the Network is to facilitate nation-wide collaborative research, promoting four intersecting research Themes: Mobile and Wireless Communications, Rural Communications, Broadband and Optical Networks, and Fundamentals of Emerging Media. Each Theme is formulated to drive multidisciplinary, innovative research as well as inspire new collaborative initiatives. Four Programs encapsulate the ....ARC Communications Research Network. Building on a strong platform of existing research excellence, the Aim of the Network is to facilitate nation-wide collaborative research, promoting four intersecting research Themes: Mobile and Wireless Communications, Rural Communications, Broadband and Optical Networks, and Fundamentals of Emerging Media. Each Theme is formulated to drive multidisciplinary, innovative research as well as inspire new collaborative initiatives. Four Programs encapsulate the core activities of the Network: Researcher Mobility, Workshops and Conferences, Postgraduate Education, and Knowledge Management Systems. The Network is expected to add significant value to pre-existing investments and raise the profile of Australian telecommunications research.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100211
Funder
Australian Research Council
Funding Amount
$650,000.00
Summary
The Big Australian Speech Corpus: An audio-visual speech corpus of Australian English. Contemporary speech science and technology are driven by the availability of large speech corpora. While audio databases exist for languages spoken in America, Europe and Japan, there is currently no large auditory-visual database of spoken language, and certainly not one for Australian English. Here we will establish the Big Australian Speech Corpus, which will support a speech science research and developmen ....The Big Australian Speech Corpus: An audio-visual speech corpus of Australian English. Contemporary speech science and technology are driven by the availability of large speech corpora. While audio databases exist for languages spoken in America, Europe and Japan, there is currently no large auditory-visual database of spoken language, and certainly not one for Australian English. Here we will establish the Big Australian Speech Corpus, which will support a speech science research and development using Australian English and facilitate the development of Australian speech technology applications from automatic speech recognition and text-to-speech synthesis used in taxi and other ordering services, to hearing prostheses and talking head aids for learning-impaired children, and a range of security and forensic applications.Read moreRead less
A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in ....A more sound approach to the neurobiology of language. How does the brain attain spoken language? Current neurobiological models assume either implicitly or explicitly that there is no relationship between a word's sound and its meaning. Yet considerable evidence shows this strong assumption about the arbitrariness of language is invalid. This project will use a combination of behavioural, neuroimaging and computational studies to characterise how the brain processes statistical regularities in sound-to-meaning correspondences as probabilistic cues to attain spoken language. The outcome will be a better neural account of language comprehension and production. The benefit of this new account will be a stronger basis for assessment and treatment of developmental and acquired language impairments.Read moreRead less
Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.Read moreRead less
Vision performance in relationship to spectacle lens design. Refractive errors such as short-sightedness, long-sightedness or presbyopia (age related decline in near vision) are the leading causes of visual impairment in the world. Of these, presbyopia affects almost 100% of the population above 45 years of age. This represents over 40% of all Australians. Although spectacles provide a safe and easy means of correcting refractive errors, they affect quality of life due to distorted vision, disco ....Vision performance in relationship to spectacle lens design. Refractive errors such as short-sightedness, long-sightedness or presbyopia (age related decline in near vision) are the leading causes of visual impairment in the world. Of these, presbyopia affects almost 100% of the population above 45 years of age. This represents over 40% of all Australians. Although spectacles provide a safe and easy means of correcting refractive errors, they affect quality of life due to distorted vision, discomfort such as head and neck ache and cosmetic effects. The goals of the project are to better understand the visual performance of young and old people who wear glasses and to develop improved spectacle lens designs to provide clear and comfortable vision over a range of distances.Read moreRead less
Learning human activities through low cost, unobtrusive RFID technology. A rapidly growing aged population presents many challenges to Australia's health and aged care services. The outcomes of this project will help aging Australians live in their own homes longer, with greater independence and safety by providing an automated, unobtrusive means for health professionals to monitor activity and intervene as required.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less