Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financi ....Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financial transactions. The technology will also assist in the protection of the community and safeguard Australia by enabling the implementation of the following: suspect identification using voice print; national security measures for combating terrorism by using voice to locate and track terrorists; preemptive criminal activity counter-measures; surveillance and secure building access by voice.Read moreRead less
Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security meas ....Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security measures for combating terrorism by using voice to locate and track terrorists. Our research at QUT Speech Research Lab is at the forefront of development in this field and will provide Australia with a technological advantage in the rapidly evolving global market for speaker recognition technology for person authentication applications.Read moreRead less
Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and a ....Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and as a component of personal identification systems to counter terrorism. The key to successful face location and recognition is an effective combination of all data - range, luminance and colour - and techniques for this will be the discovered outcomes.Read moreRead less
Automatic Ontology Learning and Data Reasoning in Web Mining. This research has an impact on both research and practical applications. In research, it provides opportunities for research students to carry out research using both data mining and data reasoning to solving Web based application problems. In practical, it can help IT industry to design the new generation of Web mining systems in order to provide invaluable service to users. This research also develops new techniques for data automa ....Automatic Ontology Learning and Data Reasoning in Web Mining. This research has an impact on both research and practical applications. In research, it provides opportunities for research students to carry out research using both data mining and data reasoning to solving Web based application problems. In practical, it can help IT industry to design the new generation of Web mining systems in order to provide invaluable service to users. This research also develops new techniques for data automatic processing within areas of smart information use in Australia. In particular it further develops data mining techniques by introducing data reasoning models for using discovered knowledge. It must be useful to improve the efficiency of the existing data mining systems. Read moreRead less
Efficient multi-context systems for heterogeneous information reasoning and sharing. This project aims to investigate formal models and efficient methods for processing information from heterogeneous sources such as the World Wide Web. When the project is successfully completed, new theories, technologies and systems for reasoning about heterogeneous knowledge bases will be developed.
Rapidly Locating Items in Distribution Networks with Process-Driven Nodes. Safety-critical product recalls are a major public health issue in Australia. Recent extortion attempts involving poisoning of chocolate bars, paracetamol tablets and biscuits have demonstrated the urgent need for improved ways of locating commercial products that have been released into the community. Existing product recall tools are effective only within regulated manufacturing and warehousing facilities. This project ....Rapidly Locating Items in Distribution Networks with Process-Driven Nodes. Safety-critical product recalls are a major public health issue in Australia. Recent extortion attempts involving poisoning of chocolate bars, paracetamol tablets and biscuits have demonstrated the urgent need for improved ways of locating commercial products that have been released into the community. Existing product recall tools are effective only within regulated manufacturing and warehousing facilities. This project will develop novel techniques for locating items in large-scale distribution networks driven by complex logistic processes. The outcomes of the project will make it easier to rapidly and accurately pinpoint product locations outside controlled facilities, thus contributing to both cost savings and public safety.Read moreRead less
Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Searching for Maximal Satisfaction. A wide range of practical problems such as scheduling, timetabling, planning and economic forecasting are not only computationally intractable in general, but often involve conflicting constraints that make them unsolvable. These problems can be represented as MaxSAT, the optimisation version of the satisfiability problem (SAT). This project aims to develop novel and efficient algorithms to address the problem of maximal satisfaction. It is proposed that these ....Searching for Maximal Satisfaction. A wide range of practical problems such as scheduling, timetabling, planning and economic forecasting are not only computationally intractable in general, but often involve conflicting constraints that make them unsolvable. These problems can be represented as MaxSAT, the optimisation version of the satisfiability problem (SAT). This project aims to develop novel and efficient algorithms to address the problem of maximal satisfaction. It is proposed that these algorithms will be implemented within prototype MaxSAT solver systems, which will be experimentally evaluated on large-sized real world optimisation problems of high economic and societal significance. These solvers are expected to also compete in the industrial track of the international SAT solving competitions.Read moreRead less
Perceptually-motivated speech parameters for concurrent coding and noise-robust distributed recognition of human speech for mobile telephony systems. With speech being a simple and natural form of communication, speech recognition technology is being widely used in mobile phones. Nowadays, consumers can interact with remote systems via spoken words. This project will develop remote speech recognition with better accuracy and noise-robustness while using the existing mobile phone infrastructure.
Automatic Brain Tissue Segmentation in Magnetic Resonance Images based on Knowledge-guided Constrained Clustering. Accurate volumetric measurement of brain tissues is of critical importance in the study of many brain disorders, disease diagnosis, disease progression tracking and treatment monitoring. The study in this research will result in the development of a powerful computational technique that allows automatic volumetric measurement and analysis of brain tissues. The software developed in ....Automatic Brain Tissue Segmentation in Magnetic Resonance Images based on Knowledge-guided Constrained Clustering. Accurate volumetric measurement of brain tissues is of critical importance in the study of many brain disorders, disease diagnosis, disease progression tracking and treatment monitoring. The study in this research will result in the development of a powerful computational technique that allows automatic volumetric measurement and analysis of brain tissues. The software developed in this project will expedite early clinical diagnosis and treatment of neural diseases for patients, hence saving life and reducing health cost both at the personal and the national level. Read moreRead less