Investigation of the component distributions of pause duration in spontaneous speech: Constraints for models of language production. We have discovered that the distribution of pause durations in spontaneous speech of individual speakers can be decomposed into at least two log-normal distributions. Our project will investigate this finding and provide a foundation for new research relevant to language production models. This will be achieved by determining the semantic, lexical, psycholinguistic ....Investigation of the component distributions of pause duration in spontaneous speech: Constraints for models of language production. We have discovered that the distribution of pause durations in spontaneous speech of individual speakers can be decomposed into at least two log-normal distributions. Our project will investigate this finding and provide a foundation for new research relevant to language production models. This will be achieved by determining the semantic, lexical, psycholinguistic, physiological, and acoustic concomitants of each component distribution and by investigating the impact of selected variables on the shape and location of each. The project has important implications for models of language production and applied problems involving automatic speech recognition, forensic speaker identification, and human communication disorders.Read moreRead less
Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result giv ....Optimal Robust Fitting under the Framework of LP-Type Problems. The project aims to develop algorithms to support the development of robust and accurate computer vision systems. Real-world visual data (images, videos) is inherently noisy and outlier prone. To build computer vision systems that work reliably in the real world, it is necessary to ensure that the underlying algorithms are robust and efficient. The project aims to devise novel algorithms that can compute the best possible result given the input data in a short amount of time. The expected outcomes would support the construction of reliable and accurate computer vision-based systems, such as large-scale 3-D reconstruction from photo collections, self-driving cars and domestic robots.Read moreRead less
Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise deve ....Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise developed from the project will provide a competitive edge for Australian industries in aerospace, oceanography, robotics, remote sensing, and biomedical engineering. Read moreRead less