Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt ex ....Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt existing adult speech recognition models for use with children and people with speaking difficulties. The intended outcomes will improve access to automatic speech recognition systems for Australians whose communication with speech-controlled environmental and educational devices is currently restricted.Read moreRead less
Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outc ....Developmental trajectory of tongue control for speech with real-time MRI. This project aims to evaluate the developmental trajectory of tongue control during speech, relating dynamic 3D vocal tract modelling to the acoustic signal. By optimising real-time MRI technology to capture and model articulatory movements, the project expects to accelerate understanding of how tongue control for speech is developed, mastered, and perturbed by factors such as rapid growth and foreign accent. Expected outcome is a new understanding of how different speakers' vocal tracts change and how speech is reshaped, informed by real physiological data. Significant benefits will be realised through refined methods and theory development for diverse fields e.g. linguistics, speech science, and automatic speech recognition/synthesis. Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less
A coupled finite volume method for viscoelastic flow problems on highly-skewed unstructured meshes: a computational rheology revolution. Commercial tools are unavailable for 21st century industry to analyse complex flow processes involving viscoelastic materials. Using fabrication of microstructured polymer optical fibre as a key case study, a coupled finite volume methodology holds the key for the next generation of computational rheology simulators.
Implementation of cognitive radar techniques in resource limited radar systems. Cognitive radar technology enables a multiple functional radar system to be built on a single chip, to be of high efficiency and low cost. Waveform design and scheduling play a key role in such a system. This project will investigate and design waveforms and scheduling methods for building a real cognitive radar system in the extremely high frequency band.
A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, th ....A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, this project seeks to develop new distributed solutions for statistical estimation, which are specifically designed for dynamic systems with multiple object states, and are inherently scalable and robust. The potential benefits include new technologies for smart cities, autonomous infrastructure, and digital productivity.Read moreRead less
A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.
Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful ....Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful visualisations, and evaluate using real world social network and biological network data sets. The new models, metrics and algorithms produced by this project will be used in the next generation Visual Analytic tools to enable analysts develop accurate insights and new knowledge of complex data.Read moreRead less
Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New ....Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New design methods that deal with noise in an optimal way;
(iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems.
The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.Read moreRead less
Multiscale modelling of systems with complex microscale detail. In modern science and engineering many complex systems are described by distinctly different microscale physical models within different regions of space. This project is to develop systematic mathematical and computational methods for the compact and accurate macroscale modelling and computation of such systems for application in industrial research and development. Our sparse simulations, justified with mathematical analysis, use ....Multiscale modelling of systems with complex microscale detail. In modern science and engineering many complex systems are described by distinctly different microscale physical models within different regions of space. This project is to develop systematic mathematical and computational methods for the compact and accurate macroscale modelling and computation of such systems for application in industrial research and development. Our sparse simulations, justified with mathematical analysis, use small bursts of particle/agent simulations, PDEs, or difference equations, to efficiently evaluate macroscale system-level behaviour. The objective is to accurately interface between disparate microscale models and establish provable predictions on how the microscale parameter spaces resolve at the macroscale.Read moreRead less